(19)
(11)EP 3 502 271 A2

(12)EUROPEAN PATENT APPLICATION

(43)Date of publication:
26.06.2019 Bulletin 2019/26

(21)Application number: 19153228.2

(22)Date of filing:  22.10.2015
(51)International Patent Classification (IPC): 
C12Q 1/68(2018.01)
G01N 33/49(2006.01)
(84)Designated Contracting States:
AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR

(30)Priority: 22.10.2014 US 201462067414 P

(62)Application number of the earlier application in accordance with Art. 76 EPC:
15853565.8 / 3210021

(71)Applicants:
  • The George Washington University, A Congressionally Chartered Not-For-Profit Corporation
    Washington, District of Columbia 20052 (US)
  • Astute Medical, Inc.
    San Diego, CA 92121-1122 (US)

(72)Inventors:
  • Chawla, Lakhmir S.
    San Diego, CA 92130 (US)
  • McCaffrey, Timothy A.
    Silver Spring, MD 20902 (US)
  • McPherson, Paul
    Encinitas, CA 92024 (US)
  • Kampf, James Patrick
    San Diego, CA 92130 (US)

(74)Representative: dompatent von Kreisler Selting Werner - Partnerschaft von Patent- und Rechtsanwälten mbB 
Deichmannhaus am Dom Bahnhofsvorplatz 1
50667 Köln
50667 Köln (DE)

  


(54)BLOOD BIOMARKERS FOR APPENDICITIS AND DIAGNOSTICS METHODS USING BIOMARKERS


(57) The invention relates to methods and kits for diagnosing and/or treating appendicitis in a subject, comprising performing one or more assays configured to detect one or more biomarkers on a body fluid sample obtained from the subject to provide one or more assay result(s) and correlating the assay result(s) to the occurrence or nonoccurrence of appendicitis in the subject or likelihood of the future outcome to the subject.




Description

CROSS-REFERENCE OF RELATED APPLICATION



[0001] This application claims priority to U.S. Provisional Application No. 62/067,414 filed October 22, 2014, the entire contents of which are hereby incorporated by reference.

BACKGROUND


1. Technical Field



[0002] The field of the currently claimed embodiments of this invention relate to methods and kits for assessing and treating abdominal discomfort/pain (the terms abdominal pain and abdominal discomfort will be used interchangeably throughout) and appendicitis in a subject, and more particularly to assessing and treating abdominal discomfort and appendicitis in a subject using the analysis of biomarkers isolated from the subject.

2. Discussion of Related Art



[0003] Abdominal pain is a major cause of hospital visits, accounting for about 10% of 62 million visits per year by adults who present at an emergency department (ED) for non-injury causes [1]. Acute appendicitis is one of the most common causes of abdominal pain and results in nearly 750,000 ED visits with approximately 250,000 appendectomies performed annually. Globally, a small but significant portion of the operations are "negative appendectomies", resulting in the removal of a non-inflamed appendix due to misdiagnosis [2-4], reported as high as 17-28% outside the US and Western Europe [5,6].

[0004] Prior to the widespread availability of computed tomography (CT) scans, the accurate diagnosis of appendicitis could be challenging, and in places where CT is still not available, the Alvarado score of clinical characteristics is a widely used diagnostic tool [5,6]. Currently in the United States, CT scanning is the 'gold standard' for the diagnosis of appendicitis, with magnetic resonance imaging (MRI) being a reasonable alternative in pregnant women [7], and ultrasound sonography being an acceptable alternative for preliminary diagnostics to avoid radiation [8]. While CT is the most sensitive and specific diagnostic tool for appendicitis [9,10], and used in almost 98% of patients undergoing appendectomy in the US [11], CT scanning carries a significant radiation exposure, and epidemiologic data suggest that radiation exposure can increase the risk of developing a future malignancy [12]. This issue is of particular concern in children because they are more sensitive to the hazards of radiation, they are among the most common patients to present to the ED with abdominal pain, and have the highest rate of misdiagnosis [10,13]. In an attempt to reduce the damaging effect of CT scans, several clinical trials are examining the diagnostic utility of lower doses of radiation, primarily in children [14-16].

[0005] In order to utilize CT scanning more appropriately, and to improve diagnosis in areas where CT scans are unavailable, blood biomarkers were identified that serve as a preliminary safe and rapid test to help identify patients with appendicitis. Genome-wide profiling of RNA transcripts in whole blood RNA of patients presenting at the ED for abdominal pain was conducted, resulting in confirmed appendicitis versus other abdominal abnormalities.

[0006] Some embodiments of the present invention include methods and kits for assessing and treating abdominal discomfort and appendicitis in a subject, and more particularly to assessing and treating abdominal discomfort and appendicitis in a subject using the analysis of biomarkers isolated from the subject.

SUMMARY



[0007] Embodiments of the invention include methods of diagnosing appendicitis in a subject, or assigning a likelihood of a future outcome to a subject diagnosed with appendicitis, comprising performing one or more assays configured to detect one or more biomarkers selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor β, Fc frag of IgG receptor IIIb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha 1B, Defensin alpha 3, 18S ribosomal RNA, CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein P1, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32 on a body fluid sample obtained from the subject to provide one or more assay result(s); and correlating the assay result(s) to the occurrence or nonoccurrence of appendicitis in the subject or likelihood of the future outcome to the subject.

[0008] Embodiments of the invention include methods for evaluating biomarker levels in a body fluid sample, comprising obtaining a body fluid sample from a subject selected for evaluation based on a determination that the subject is experiencing symptoms indicative of possible acute appendicitis; and performing one or more analyte binding assays configured to detect one or more biomarkers selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor β, Fc frag of IgG receptor IIIb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha 1B, Defensin alpha 3, 18S ribosomal RNA, CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein P1, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32 by introducing the body fluid sample obtained from the subject into an assay instrument which (i) contacts the body fluid sample with one or more binding reagents corresponding to the biomarker(s) being assayed, wherein each biomarker which is assayed binds to its respective specific binding reagent in an amount related to its concentration in the body fluid sample, (ii) generates one or more assay results indicative of binding of each biomarker which is assayed to its respective specific binding reagent; and (iii) displays the one or more assay results as a quantitative result in a human-readable form.

[0009] Embodiments of the invention include systems for evaluating biomarker levels, comprising a plurality of reagents which specifically bind for detection a plurality of biomarkers selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor β, Fc frag of IgG receptor IIIb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha 1B, Defensin alpha 3, 18S ribosomal RNA, CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein P1, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32; an assay instrument configured to (i) receive a body fluid sample, (ii) contact the plurality of reagents with the body fluid sample and (iii) generate and quantitatively display in human readable form one or more assay results indicative of binding of each biomarker which is assayed to a respective specific binding reagent in the plurality of reagents.

[0010] Embodiments of the invention include uses of one or more reagents which specifically bind for detection one or more biomarkers selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor β, Fc frag of IgG receptor IIIb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha 1B, Defensin alpha 3, 18S ribosomal RNA, CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein P1, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32 for the diagnosis of appendicitis.

[0011] Embodiments of the invention include uses of one or more biomarkers selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor β, Fc frag of IgG receptor IIIb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha 1B, Defensin alpha 3, 18S ribosomal RNA, CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein P1, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32 for the diagnosis of appendicitis.

BRIEF DESCRIPTION OF THE DRAWINGS



[0012] Further objectives and advantages will become apparent from a consideration of the description, drawings, and examples.

FIGURE 1 is a scatterplot of the expression patterns in 2 groups of patients.

FIGURE 2 shows hierarchical clustering of 37 differentially expressed genes in appendicitis patients.

FIGURE 3 shows a graph displaying the Partial Least Squares Discriminant (PLSD) Model for classification of appendicitis from RNA biomarkers.

FIGURE 4 is a graph showing results of defensins in appendicitis, hernia, and lower respiratory infection patients.

FIGURE 5 shows the behavior of selected transcripts in a validation cohort.

FIGURE 6 shows a schematic of a model of appendicitis biomarker pathophysiology.

FIGURE 7 shows a graph showing microarray and quantitative reverse-transcription polymerase chain reaction results for 3 genes differentially expressed in subjects with appendicitis.

FIGURE 8 shows a Receiving Operating Characteristic (ROC) curve with data from 3 gene transcripts.


DETAILED DESCRIPTION



[0013] In some embodiments, the invention relates to a method of diagnosing appendicitis in a subject, or assigning a likelihood of a future outcome to a subject diagnosed with appendicitis, comprising performing one or more assays configured to detect one or more biomarkers selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor β, Fc frag of IgG receptor IIIb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha 1B, Defensin alpha 3, 18S ribosomal RNA, CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein P1, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32 on a body fluid sample obtained from the subject to provide one or more assay result(s); and correlating the assay result(s) to the occurrence or nonoccurrence of appendicitis in the subject or likelihood of the future outcome to the subject.

[0014] In some embodiments, the invention relates to the method above, wherein the performing step comprises introducing the body fluid sample obtained from the subject into an assay instrument which (i) contacts the body fluid sample with one or more binding reagents corresponding to the biomarker(s) being assayed, wherein each biomarker which is assayed binds to its respective specific binding reagent in an amount related to its concentration in the body fluid sample, (ii) generates one or more assay results indicative of binding of each biomarker which is assayed to its respective specific binding reagent; and (iii) displays the one or more assay results as a quantitative result in a human-readable form.

[0015] In some embodiments, the invention relates to the method above, wherein the specific binding reagent is an antibody.

[0016] In some embodiments, the invention relates to the method above, wherein the one or more assays are sandwich assays.

[0017] In some embodiments, the invention relates to the method above, wherein the correlating step comprises comparing the assay result(s) or a value derived therefrom to a threshold selected in a population study to separate the population into a first subpopulation at higher predisposition for the occurrence of appendicitis or the future outcome, and a second subpopulation at lower predisposition for the occurrence of appendicitis or the future outcome relative to the first subpopulation.

[0018] In some embodiments, the invention relates to the method above, and further comprises treating the subject based on the predetermined subpopulation of individuals to which the patient is assigned, wherein if the patient is in the first subpopulation, the treatment comprises treating the subject for appendicitis or the future outcome.

[0019] In some embodiments, the invention relates to the method above, wherein the future outcome is mortality.

[0020] In some embodiments, the invention relates to the method above, wherein the subject is being evaluated for abdominal pain.

[0021] In some embodiments, the invention relates to the method above, wherein the correlating step comprises determining the concentration of each biomarker which is assayed, and individually comparing each biomarker concentration to a corresponding threshold level for that biomarker.

[0022] In some embodiments, the invention relates to the method above, wherein the assay instrument comprises a processing system configured to perform the correlating step and output the assay result(s) or a value derived therefrom in human readable form.

[0023] In some embodiments, the invention relates to the method above, wherein a plurality of the biomarkers are measured, wherein the assay instrument performs the correlating step, which comprises determining the concentration of each of the plurality of biomarkers, calculating a single value based on the concentration of each of the plurality of biomarkers, comparing the single value to a corresponding threshold level and displaying an indication of whether the single value does or does not exceed its corresponding threshold in a human-readable form.

[0024] In some embodiments, the invention relates to the method above, wherein method provides a sensitivity or specificity of at least 0.7 for the identification of appendicitis when compared to normal subjects.

[0025] In some embodiments, the invention relates to the method above, wherein method provides a sensitivity or specificity of at least 0.7 for the identification of appendicitis when compared to subjects exhibiting symptoms that mimic appendicitis symptoms.

[0026] In some embodiments, the invention relates to the method above, wherein the sample is selected from the group consisting of blood, serum, and plasma.

[0027] In some embodiments, the invention relates to the method above, wherein the sample is urine.

[0028] In some embodiments, the invention relates to a method for evaluating biomarker levels in a body fluid sample, comprising obtaining a body fluid sample from a subject selected for evaluation based on a determination that the subject is experiencing symptoms indicative of possible acute appendicitis; and performing one or more analyte binding assays configured to detect one or more biomarkers selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor β, Fc frag of IgG receptor IIIb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha 1B, Defensin alpha 3, 18S ribosomal RNA, CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein P1, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32 by introducing the body fluid sample obtained from the subject into an assay instrument which (i) contacts the body fluid sample with one or more binding reagents corresponding to the biomarker(s) being assayed, wherein each biomarker which is assayed binds to its respective specific binding reagent in an amount related to its concentration in the body fluid sample, (ii) generates one or more assay results indicative of binding of each biomarker which is assayed to its respective specific binding reagent; and (iii) displays the one or more assay results as a quantitative result in a human-readable form.

[0029] In some embodiments, the invention relates to the method above, wherein the assay result(s) are displayed as a concentration of each biomarker which is assayed.

[0030] In some embodiments, the invention relates to the method above, wherein the assay instrument further individually compares each biomarker concentration to a corresponding threshold level for that biomarker, and displays an indication of whether each biomarker does or does not exceed its corresponding threshold in a human-readable form.

[0031] In some embodiments, the invention relates to the method above, wherein a plurality of the biomarkers are measured, and wherein the assay results(s) comprise a single value calculated using a function that converts the concentration of each of the plurality of biomarkers into a single value.

[0032] In some embodiments, the invention relates to the method above, wherein the assay instrument further compares the single value to a corresponding threshold level and displays an indication of whether the single value does or does not exceed its corresponding threshold in a human-readable form.

[0033] In some embodiments, the invention relates to the method above, wherein the subject is selected for evaluation of a mortality risk within a period selected from the group consisting of 21 days, 14 days, 7 days, 5 days, 96 hours, 72 hours, 48 hours, 36 hours, 24 hours, and 12 hours.

[0034] In some embodiments, the invention relates to the method above, wherein the plurality of assays are immunoassays performed by (i) introducing the body fluid sample into an assay device comprising a plurality of antibodies, at least one of which binds to each biomarker which is assayed, and (ii) generating an assay result indicative of binding of each biomarker to its respective antibody.

[0035] In some embodiments, the invention relates to a system for evaluating biomarker levels, comprising a plurality of reagents which specifically bind for detection a plurality of biomarkers selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor β, Fc frag of IgG receptor IIIb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha 1B, Defensin alpha 3, 18S ribosomal RNA, CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein P1, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32; an assay instrument configured to (i) receive a body fluid sample, (ii) contact the plurality of reagents with the body fluid sample and (iii) generate and quantitatively display in human readable form one or more assay results indicative of binding of each biomarker which is assayed to a respective specific binding reagent in the plurality of reagents.

[0036] In some embodiments, the invention relates to the system above, wherein the reagents comprise a plurality of antibodies, at least one of which binds to each of the biomarkers which are assayed.

[0037] In some embodiments, the invention relates to the system above, wherein assay instrument comprises an assay device and an assay device reader, wherein the plurality of antibodies are immobilized at a plurality of predetermined locations within the assay device, wherein the assay device is configured to receive the body fluid sample such that the body fluid sample contacts the plurality of predetermined locations, and wherein the assay device reader interrogates the plurality of predetermined locations to generate the assay results.

[0038] In some embodiments, the invention relates to a use of one or more reagents which specifically bind for detection one or more biomarkers selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor β, Fc frag of IgG receptor IIIb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha 1B, Defensin alpha 3, 18S ribosomal RNA, CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein P1, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32 for the diagnosis of appendicitis.

[0039] In some embodiments, the invention relates to a use of one or more biomarkers selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor β, Fc frag of IgG receptor IIIb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha 1B, Defensin alpha 3, 18S ribosomal RNA, CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein P1, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32 for the diagnosis of appendicitis.

Definitions



[0040] To facilitate an understanding of the present invention, a number of terms and phrases are defined below.

[0041] As used herein, the singular forms "a", "an", and "the" include plural forms unless the context clearly dictates otherwise. Thus, for example, reference to "a binding agent" includes reference to more than one binding agent.

[0042] The terms "diagnostic" and "diagnosis" refer to identifying the presence or nature of a pathologic condition and includes identifying patients who are at risk of developing a specific disease or disorder. Diagnostic methods differ in their sensitivity and specificity. The "sensitivity" of a diagnostic assay is the percentage of diseased individuals who test positive (percent of "true positives"). Diseased individuals not detected by the assay are "false negatives." Subjects who are not diseased and who test negative in the assay, are termed "true negatives." The "specificity" of a diagnostic assay is 1 minus the false positive rate, where the "false positive" rate is defined as the proportion of those without the disease who test positive. While a particular diagnostic method may not provide a definitive diagnosis of a condition, it suffices if the method provides a positive indication that aids in diagnosis.

[0043] The terms "detection", "detecting" and the like, may be used in the context of detecting biomarkers, or of detecting a disease or disorder (e.g., when positive assay results are obtained). In the latter context, "detecting" and "diagnosing" are considered synonymous.

[0044] The terms "subject", "patient" or "individual" generally refer to a human, although the methods of the invention are not limited to humans, and should be useful in other mammals (e.g., cats, dogs, etc.).

[0045] "Sample" is used herein in its broadest sense. A sample may comprise a bodily fluid including blood, serum, plasma, tears, aqueous and vitreous humor, spinal fluid, urine, and saliva; a soluble fraction of a cell or tissue preparation, or media in which cells were grown. Means of obtaining suitable biological samples are known to those of skill in the art.

[0046] An "antibody" is an immunoglobulin molecule that recognizes and specifically binds to a target, such as a protein, polypeptide, peptide, carbohydrate, polynucleotide, lipid, etc., through at least one antigen recognition site within the variable region of the immunoglobulin molecule. As used herein, the term is used in the broadest sense and encompasses intact polyclonal antibodies, intact monoclonal antibodies, antibody fragments (such as Fab, Fab', F(ab')2, and Fv fragments), single chain Fv (scFv) mutants, multispecific antibodies such as bispecific antibodies generated from at least two intact antibodies, hybrid antibodies, fusion proteins comprising an antibody portion, and any other modified immunoglobulin molecule comprising an antigen recognition site so long as the antibodies exhibit the desired biological activity. An antibody may be of any the five major classes of immunoglobulins: IgA, IgD, IgE, IgG, and IgM, or subclasses (isotypes) thereof (e.g. IgG1, IgG2, IgG3, IgG4, IgA1 and IgA2), based on the identity of their heavy-chain constant domains referred to as alpha, delta, epsilon, gamma, and mu, respectively. The different classes of immunoglobulins have different and well known subunit structures and three-dimensional configurations. Antibodies may be naked or conjugated to other molecules such as toxins, radioisotopes, etc.

[0047] The term "antibody fragments" refers to a portion of an intact antibody. Examples of antibody fragments include, but are not limited to, linear antibodies; single-chain antibody molecules; Fc or Fc' peptides, Fab and Fab fragments, and multispecific antibodies formed from antibody fragments.

[0048] "Hybrid antibodies" are immunoglobulin molecules in which pairs of heavy and light chains from antibodies with different antigenic determinant regions are assembled together so that two different epitopes or two different antigens may be recognized and bound by the resulting tetramer.

[0049] "Isolated" in regard to cells, refers to a cell that is removed from its natural environment and that is isolated or separated, and is at least about 30%, 50%, 75%, and 90% free from other cells with which it is naturally present, but which lack the marker based on which the cells were isolated.

[0050] For use in the diagnostic and therapeutic applications described herein, kits are also within the scope of the invention. Such kits can comprise a carrier, package or container that is compartmentalized to receive one or more containers such as vials, tubes, and the like, each of the container(s) comprising one of the separate elements to be used in the method. For example, the container(s) can comprise a probe that is or can be detectably labeled. The probe can be an antibody or polynucleotide specific for a biomarker of interest. Alternatively, the kit can comprise a mass spectrometry (MS) probe. The kit can also include containers containing nucleotide(s) for amplification or silencing of a target nucleic acid sequence, and/or a container comprising a reporter means, such as a biotin-binding protein, e.g., avidin or streptavidin, bound to a detectable label, e.g., an enzymatic, florescent, or radioisotope label. The kit can include all or part of the amino acid sequence of the biomarker, or a nucleic acid molecule that encodes such amino acid sequences.

[0051] The kit of the invention will typically comprise the container described above and one or more other containers comprising materials desirable from a commercial and user standpoint, including buffers, diluents, filters, needles, syringes, and package inserts with instructions for use. In addition, a label can be provided on the container to indicate that the composition is used for a specific therapeutic or non-therapeutic application, and can also indicate directions for either in vivo or in vitro use, such as those described above. Directions and or other information can also be included on an insert which is included with the kit.

[0052] Polynucleotides may be prepared using any of a variety of techniques known in the art. The polynucleotide sequences selected as probes (and bind to the biomarkers of interest) should be sufficiently long and sufficiently unambiguous that false positives are minimized. The polynucleotide is preferably labeled such that it can be detected upon hybridization to DNA and/or RNA in the assay being screened. Methods of labeling are well known in the art, and include the use of radiolabels, such as 32P-labeled ATP, biotinylation, fluorescent groups or enzyme labeling. Hybridization conditions, including moderate stringency and high stringency, are well known in the art.

[0053] Polynucleotide variants may generally be prepared by any method known in the art, including chemical synthesis by, for example, solid phase phosphoramidite chemical synthesis. Modifications in a polynucleotide sequence may also be introduced using standard mutagenesis techniques, such as oligonucleotide-directed site-specific mutagenesis. Alternatively, RNA molecules may be generated by in vitro or in vivo. Certain portions may be used to prepare an encoded polypeptide.

[0054] Any polynucleotide may be further modified to increase stability in vivo and/or in vitro for improved activity and/or storage. Possible modifications include, but are not limited to, the addition of flanking sequences at the 5' and/or 3' ends; the use of phosphorothioate or 2' 0-methyl rather than phosphodiesterase linkages in the backbone; and/or the inclusion of nontraditional bases such as inosine, queosine and wybutosine, as well as acetyl- methyl-, thio- and other modified forms of adenine, cytidine, guanine, thymine and uridine.

[0055] Polynucleotides and/or antibodies specific to biomarkers of interest can be conjugated to detectable markers to a second molecule. Suitable detectable markers include, but are not limited to, a radioisotope, a fluorescent compound, a bioluminescent compound, chemiluminescent compound, a metal chelator or an enzyme. A second molecule for conjugation can be selected in accordance with the intended use. For example, for therapeutic use, the second molecule can be a toxin or therapeutic agent. Further, bi-specific antibodies specific for two or more biomarkers may be generated using methods generally known in the art. Homodimeric antibodies may also be generated by cross-linking techniques known in the art.

EXAMPLES



[0056] The following examples help explain some concepts of the current invention. However, the general concepts of the current invention are not limited to the particular examples.

Example 1: Acute Appendicitis: Transcript Profiling of Blood Identifies Promising Biomarkers and Potential Underlying Processes


Materials and Methods


Subjects.



[0057] Ethics statement: The protocol of this observational study was approved by the Institutional Review Board of The George Washington University, and all subjects gave informed consent. From a cohort of 270 patients presenting to the ED for various reasons, a subset of 40 subjects with a principal complaint of abdominal pain, and who met inclusion/exclusion criteria, were identified, and divided into a discovery set of 20 patients, and a validation set of 20 patients for transcript profiling of whole blood RNA by microarray.

[0058] Discovery Set: For the discovery set, we employed 20 subjects who presented to the ED who were undergoing CT scanning. In order to meet criteria, the patient undergoing the CT scan must have had appendicitis suspected in the differential diagnosis. Appendicitis Patients: Patients with appendicitis were diagnosed by CT scanning (n=11), and had research blood samples drawn by venipuncture after anesthetic induction, but prior to skin incision for appendectomy. All cases of appendicitis were confirmed by intra-operative findings and pathology of the removed appendix. Control Patients: Patients included in the control arm (n=9) were patients who were found not to have appendicitis, by both CT scanning and clinical follow-up. This included patients with reported abdominal pain, later found to be caused by diverticulitis, or other gastrointestinal pathologies, but not clinically associated with appendicitis. Blood was drawn at study enrollment for these patients.

[0059] Validation Set: Control Patients. Because appendicitis can involve infection, we enrolled 5 patients with lower respiratory tract infections (LRI) in the ED as an 'infection' control. Also, as a control for surgical factors, we enrolled 5 patients undergoing elective ventral hernia or inguinal hernia repair (HER), and these were compared with 10 new patients with surgically confirmed appendicitis (APP). In all surgical patients, including appendicitis and hernia repairs, research blood samples were drawn by venipuncture after anesthetic induction, and prior to skin incision. Two patients, (1 HER, 1 APP) were excluded due to technical complications in RNA purification or microarray analysis.

Blood samples.



[0060] Blood was drawn in 3.2% sodium citrate tubes for frozen plasma samples, in Tempus Blood RNA tubes (ABI) for genome-wide RNA profiling, and in BD Vacutainer K2 tubes for complete blood counts with differentials.

RNA purification for transcript profiling.



[0061] Tempus Blood RNA preservation tubes were stored at -80° C and then thawed at 37° C prior to processing according to manufacturer's methods. Total RNA was purified from whole blood using Tempus Blood RNA kit (ABI), followed by an aggressive DNAse treatment. Briefly, the preserved whole blood was pelleted at 3000 x g for 30 minutes in a 4°C refrigerated centrifuge, redissolved in lysis buffer and nucleic acids were bound to a column. After washing, nucleic acids were eluted with RNAse/DNAse free water and quantified by with NanoDrop ND-1000 spectrophotometer. DNA was eliminated by aggressive DNAse treatment (TurboDNAse, Ambion) at 2 U/10 µg nucleic acids, followed by affinity removal of the DNAse. The remaining RNA was quantified and RNA integrity was evaluated by 260/280 ratio on ND-1000 and by capillary electrophoresis on a Bioanalyzer 2100 (Agilent). RIN scores >7 were considered acceptable for further sample processing and did not differ between groups.

Microarray Expression Profiling and Analysis.



[0062] Purified RNA (100 ng) was labeled with the Illumina cRNA synthesis kit and hybridized to Illumina Human HT-12v4 Expression BeadChip arrays (http://www.illumina.com/products/humanht_12_expression_beadchip_kits_v4.html) containing more than 47,000 probes derived from the NCBI RefSeq release 38 (http://www.ncbi.nlm.nih.gov/refseq/). The arrays were washed and then fluorescence was quantitated on an Illumina HiScan (http://www.illumina.com/systems/hiscan.html).

[0063] The fluorescence levels per bead were converted to transcript levels using Illumina GeneStudio, which averaged typically 30 beads per transcript to produce a mean expression level for each of the 46K transcripts. Raw BeadChip fluorescence values were imported into GeneSpring GX12.5 with normalization to the 75-percentile of expression, but without baseline transformation. The main effect of identifying differentially expressed genes (DEG) with respect to appendicitis versus controls was achieved by a combined filter for a p value <0.05 on t test without correction for multiple testing, and 2) fold change > 2.0. The DEG list was further analyzed for gene ontologies using DAVID [17]. Using the DEG list, a partial least squares discriminant (PLSD) prediction model was built in GeneSpring and internally validated with a Leave One Out Cross Validation (LOOCV) algorithm. The PLSD model was externally tested by applying the algorithm to a separate validation set of microarray samples not involved in building the model.

[0064] The PLSD model described here can be replicated by one of ordinary skill in the art by entering the PLSD loading weights for the genes disclosed in Tables 2 and 3 (below) into a suitable statistical package; in the instant invention, GeneSpring GX13 (Agilent) was used (http://www.genomics.agilent.com/en/productjsp?cid=AG-PT-130&tabld=AG-PR-1061&_requestid=163669). Tables 5A and 5B below summarizes the loading weights for the genes of Table 2 and Table 3.

Results


Clinical Parameters.



[0065] As shown in Table 1, the clinical parameters between patients presenting with appendicitis versus other abdominal indications in the discovery set were generally similar. Age, gender, and body mass index (BMI) were comparable, although the appendicitis patients were principally of Caucasian race. Notably, white blood cell (WBC) counts were comparable, but appendicitis patients had 10% higher neutrophil count that was not statistically significant (77.18% vs 70%, NS). Appendicitis patients had significantly lower blood creatinine level (0.78 vs 1.54 mg/dL, p=0.03 uncorrected). The two groups did not yield significantly different RNA quantities from blood, and the amplification of RNA for microarray labeling was similar.
Table 1: Clinical Parameters of Discovery Set
   Appy (11)ABD (9)
Gender   %male 55.00 55
Age Mean Years 40.73 45.89
SD   15.45 15.54
BMI Mean   24.51 26.44
SD   4.92 4.48
Race   %White 100.00 55.56
  %Black 0.00 44.44
Smoker   % 18.18 11.11
Duration of Symptom Mean Hours 29.45 32.75
SD   18.68 30.65
Temperature Mean Celsius 36.97 36.8
SD   0.47 0.38
WBC Mean K/ul 13.06 13.23
SD   6.44 30.65
Elevated Neutrophils >75% % 55.00 37.5
Neutrophils Mean %WBC 77.18 70
  SD   8.76 10.14
Creatinine Mean   0.78 1.54
SD   0.13 1.06
pH <7.35 % 0.00 11.11
Na < 130   % 0.00 0.00
HCT < 30   % 0.00 11.11
Glu > 250   % 0.00 0.00
BUN > 30   % 0.00 0.00
Immunosupressed   % 0 0
Steroids   % 0 0
Antibiotic use   % 0 0
Oral Rehydration Therapy Mean % 35.60 ND
SD   10.74 ND
Cirrhosis   % 0 0
Cancer   % 0 0
Total RNA conc. Mean ng/ul 102.36 66.48
SD   72.49 34.06
Folds amp. Mean Fold 67.96 64.13
SD   60.48 35.81
Defensin Score Mean RNA level 1.26 2.62*
  SD   0.92 1.46
*indicates p<0.05 (uncorrected probability)
% indicates the percent of patients exhibiting that trait, unless otherwise indicated


[0066] Identification of RNA biomarkers for appendicitis in whole blood.

[0067] A scatterplot of the expression patterns in the 2 groups (Figure 1) suggested that there was excellent linearity of quantitation over roughly 7 log2 orders of magnitude, with globins being the most highly and identically expressed transcripts between groups. By comparing the expression profiles of the two groups, and filtering for both a t-test probability <0.05 and a fold-change of >2.0, 37 transcripts were identified as significantly differentially expressed (Table 2, above). Hierarchical clustering of the 37 DEG was conducted to observe the pattern of covariance of the transcripts in these patients. A heatmap of the expression of these 37 transcripts across all 20 patients in the discovery set is shown in Figure 2.

[0068] Figure 1 shows a scatterplot of transcript levels in patients with appendicitis. In Figure 1, whole blood RNA from patients with acute, surgically confirmed appendicitis (n=11) or abdominal pain (n=9) was profiled for the expression level of 45,966 transcripts on Illumina BeadChip Arrays (12v4). The expression level of each transcript was averaged within groups and plotted on a log2 scale to reveal transcripts which differ between more than 2-fold between groups (outside parallel lines).

[0069] Figure 2 shows hierarchical clustering of 37 differentially expressed genes in appendicitis patients. In Figure 6, transcripts which differed between groups by >2-fold with a t-test probability of <0.05 (uncorrected) were identified by combined filtering. Following a pergene normalization, DEGs were subjected to hierarchical clustering to identify patterns of covariance among the transcripts. The upper block of transcripts from HLA-DRB5 to CA4 are relatively higher in APP patients (red) compared to patients with other types of abdominal pain (yellow to blue). Conversely, transcripts from defensins (DEFA) and ribosomal transcripts, were relatively lower in APP than abdominal pain patients.
Table 2: Differentially expressed genes (DEG) sorted by functional grouping
  Fold Expression Level   
Probe IDp ValChange ABDOMAPPDX DEFINITIONSYMBOL
         
CHEMOKINES and IMMUNE-RELATED    
3440669 0.008 2.02 1.85 2.86   Chemokine C-X-C receptor 1 CXCR1
2900327 0.003 2.59 2.80 4.17   Interleukin 8 receptor, β (CXCR2) IL8RB
1450139 0.004 3.07 3.17 4.79   Fc frag of IgG receptor IIIb (CD16b) FCGR3B
6370315 0.017 3.16 -0.11 1.55   MHC class II, DR beta 5 HLA-DRB5
6110037 0.007 2.36 2.38 3.62   Leukocyte IgG-like receptor A3 LILRA3
                 
DEFENSINS       
4540239 0.019 2.80 3.39 1.91   Defensin, alpha 1 DEFA1
870477 0.024 2.29 2.60 1.40   Defensin, alpha 1B (3 probesets) DEFA1B
2970747 0.017 2.69 2.58 1.15   Defensin, alpha 3, neutrophil-spec. DEFA3
                 
TRANSLATION and PROTEIN SYNTHESIS   
3180609 0.002 2.69 1.04 2.47   18S ribosomal RNA, non-coding 18S rRNA
6280504 0.005 2.05 1.20 2.23   28S ribosomal RNA, non-coding 28S rRNA
3190348 0.007 2.01 2.16 1.15   60S acidic ribosomal protein P1 RPLP1
6270307 0.006 2.04 2.04 1.01   40S ribosomal protein S26 (3 sets) RPS26
380575 0.000 2.14 1.49 0.39   Ribosomal protein L23 RPL23
990273 0.012 2.48 3.39 2.08   Ribosomal protein L37a RPL37A
650349 0.008 2.00 2.20 1.19   Ribosomal protein S28 RPS28
                 
STRESS and INJURY RELATED     
6100356 0.002 2.84 3.63 5.14   Alkaline phosphatase, liver/bone ALPL
6380672 0.001 2.11 1.42 2.50   Carbonic anhydrase IV CA4
1510681 0.012 2.01 3.56 2.55   Neuroblastoma breakpt family 10 NBPF10
7380706 0.001 2.10 2.61 3.68   Ninjurin 1 NINJ1
1030463 0.004 2.49 3.30 4.62   Prokineticin 2 PROK2
3890326 0.011 2.02 3.43 4.44   Superoxide dismutase 2, mitochon. SOD2
                 
MINIMALLY ANNOTATED     FROM NCBI
6420563 0.023 2.00 3.85 2.85   LOC100129902 RPS29P11
650735 0.001 2.09 1.86 0.79   LOC100131205 RPL21P28
6650603 0.000 2.66 1.95 0.54   LOC100131905 RPS27P21
7150414 0.003 2.31 2.26 1.06   LOC100132291 RPS27P29
4670634 0.003 2.81 1.69 3.18   LOC100132394 retired
6580017 0.009 2.18 2.81 1.69   LOC100132742 RPL17L
2630347 0.001 2.04 1.17 2.21   LOC100134364 retired
3390674 0.002 2.01 2.11 1.10   LOC391370 RPS12P4
1170551 0.001 2.19 1.55 0.42   LOC646785 RPS10P13
6960373 0.013 2.00 2.23 1.23   LOC644191 RPS26P8
4540241 0.005 2.15 1.10 2.21   C5orf32 CYSTM1
Table 3: A sixteen transcript set predictive of appendicitis
PROBE_IDSYMBOLProbeIDpFC (abs)ChangeABDOM expression levelAPP expression level
ILMN_1701603 ALPL 6100356 0.001874699 2.84 up 3.63 5.14
ILMN_1761566 C5orf32 4540241 0.004890986 2.15 up 1.10 2.21
ILMN_1697499 HLA-DRB5 6370315 0.017076675 3.16 up -0.11 1.55
ILMN_1680397 IL8RB 2900327 0.002848122 2.59 up 2.8 4.17
ILMN_1661631 LILRA3 6110037 0.007226919 2.36 up 2.38 3.62
ILMN_3243593 LOC100008588 3180609 0.001715004 2.69 up 1.04 2.47
ILMN_1733559 LOC100008589 6280504 0.005007231 2.05 up 1.2 2.23
ILMN_3249578 LOC100132394 4670634 0.003334389 2.81 up 1.69 3.18
ILMN_3246805 LOC100134364 2630347 8.80E-04 2.04 up 1.17 2.21
ILMN_3293367 LOC391370 3390674 0.001937386 2.01 down 2.11 1.1
ILMN_3209193 LOC644191 6960373 0.012769181 2.00 down 2.23 1.23
ILMN_2155719 NBPF10 1510681 0.012251468 2.01 down 3.56 2.55
ILMN_1815086 NINJ1 7380706 7.91E-04 2.10 up 2.61 3.68
ILMN_1775257 PROK2 1030463 0.004478186 2.49 up 3.3 4.62
ILMN_1755115 RPL23 380575 9.09E-05 2.14 down 1.49 0.39
ILMN_2336781 SOD2 3890326 0.010532255 2.02 up 3.43 4.44


[0070] Certain aspects of this expression pattern increase the confidence that some of these changes are non-random: 1) multiple probe sets identifying the same transcript (DEFA1), 2) 'hits' on highly related transcripts such as DEFA1 and DEFA3, as well as CXCR1 (aka IL8 receptor α) and IL8 receptor β.
Table 4: DEG gene symbols and Genbank IDs
Probe IDGene SymbolDefinitionGenbank ID(s)
6100356 ALPL Homo sapiens alkaline phosphatase, liver/bone/kidney (ALPL), transcript variant 1, mRNA. AL592309 AB011406
  BC066116
  AB012643
  BC136325
        NM_000478
        NM_001127501
        AL359815
        X53750
        BC021289
        AB209814
        D87880
        D87882
        D87881
        AK298085
        M24429
        BC126165
        M24428
        BC110909
        D87877
        D87887
        D87876
        CH471134
        D87888
        D87879
        D87889
        D87878
        D87883
        AK312667
        D87884
        DA625627
        D87875
        D87885
        D87874
        D87886
        DA631560
        M24435
        M24434
  M24433
  M24432
  BC090861
  M24431
  M24430
  AK293184
  M24439
  M24438
  M24437
  M24436
  AK295608
  X14174
  AK097413
4540241 C5orf32 Homo sapiens chromosome 5 open reading frame 32 (C5orf32), mRNA. BC023982 AJ245877
  CH471062
  BM919999
  AC011379
  CR607630
  AK225992
  BC013643
  AK312045
  CA310907
  CR615127
  CR603819
  AC011380
  NM_032412
6380672 CA4 Homo sapiens carbonic anhydrase IV (CA4), mRNA. AK298710 AC025048
  NM_000717
  M83670
  AK289715
        BC069649
        DA113846
        L10953
        L10954
        L10955
        L10951
        AI990988
        BC074768
        CH471109
        BC057792
        CR541766
      CR542029 AY916763
        AY916764
        AY916762
        CR541994
        BC072397
        DQ894895
        L19591
        L19592
        AB032732
        AY651785
        M68932
        U11871
        AY916766
        U11870
        CR617846
        AY916765
        BC028221
        X65858
    Homo sapiens chemokine (C-X-C motif) receptor 1 (CXCR1), mRNA.   AK312668
3440669 CXCR1   AB032730
        AB032731
        AY916769
        CH471063
        NM_000634
        AY916772
        AY916773
        AC097483
        AK298647
        AB032729
        AB032728
        AK309632
        CA425329
        DQ891718
      AX405718 L12690
        NM_004084
        AF238378
        AF200455
        BC069423
        X52053
        AF233439
        M26602
        BC093791
        DQ896798
        DQ890546
        DQ890545
        NM_001042500
        BC112188
4540239 DEFA1 Homo sapiens defensin, alpha 1 (DEFA1), mRNA.   M21130
870477 DEFA1B Homo sapiens defensin, alpha 1B (DEFA1B), mRNA. AX405718 L12690
  NM_004084
  AF238378
        AF200455
        BC069423
        X52053
        AF233439
        M26602
        BC093791
        DQ896798
        DQ890546
        DQ890545
        NM_001042500
        BC112188
        M21130
      AX405718 L12690
        NM_004084
        AF238378
        AF200455
        BC069423
        X52053
        AF233439
        M26602
        BC093791
        DQ896798
        DQ890546
        DQ890545
        NM_001042500
    Homo sapiens defensin, alpha 1B (DEFA1B), mRNA.   BC112188
4860128 DEFA1B   M21130
7150170 DEFA1B Homo sapiens defensin, alpha 1B (DEFA1B), mRNA. AX405718 L12690
  NM_004084
  AF238378
  AF200455
        BC069423
        X52053
        AF233439
        M26602
        BC093791
        DQ896798
        DQ890546
        DQ890545
        NM_001042500
        BC112188
      M21130
      L12691 EU176174
        M23281
        X13621
        NM_005217
        AF238378
        BC027917
        AF200455
    Homo sapiens defensin, alpha 3, neutrophil-specific (DEFA3), mRNA.   M21131
2970747 DEFA3   BC119706
        AK316565 M24854
        AL451067
        BC128562
        NM_000570
        X07934
        AB032414
        Z46223
        AK313219
    Homo sapiens Fc fragment of IgG, low affinity IIIb, receptor (CD16b) (FCGR3B), mRNA.   X16863
      DA672763
1450139 FCGR3B   AJ581669 J04162
        AB025256
      AF112878 Y17695
        AF112877
        X65585
        AF243537
        AY050211
        AF029286
        U68391
        AF029285
        AY465115
        AF029282
        AY050208
        AF029283
        AY050207
        M98436
        M16955
        AF327742
        M16954
        AF029281
        M16956
        AY663412
        DQ835614
        AY770514
        M63216
        AF011786
        AY267905
        AF029267
        AJ251984
    Homo sapiens major histocompatibility complex, class II, DR beta 5 (HLA-DRB5), mRNA.   M77671
      AY396024
6370315 HLA-DRB5   AY267906
        AF029273
        AF029274
        AF029275
        DQ837166
        AJ783982
        AY050214
        AF029270
        AB112913
        AF029271
        AB112912
        AF029272
        AY770520
        AJ242985
        AY663404
        U79027
        U79025
        U79026
        AF288212
        X99841
        U59685
        AL713966
        M91001
        D13412
        AY641577
        X64544
        AJ566209
        AF335232
        U34602
        X64548
        Y13727
        X64549
        AF029291
        AJ252281
        AY141137
        EF078986
        AY052549
        AY884215
        AJ506752
        AM231063
        AJ534885
        AJ512947
        M74032
        M16086
        X87210
        M63197
        M20429
        AJ427352
        AY247411
        AY502108
        M15839
        Y17819
        AF335230
        L26306
        X99895
        U25638
        AF047350
        M57600
        AY172512
        DQ987876
        AY179368
        AY179367
        AY179366
        AJ491301
        AJ867236
        U95818
        U41634
        M14661
        AJ506201
        AF034858
        EF419344
        D14352
        AF406781
        D88310
        U72264
        AJ878425
        AJ249726
        DQ514604
        DQ525634
        AJ854064
        U66721
        AY899913
        AJ245714
        AJ245715
        AJ245717
        AM000036
        X95656
        U66826
        AJ243897
        AY277387
        AJ243898
        AJ580838
        M27689
        AJ311892
        AF247534
        AF247533
        U37583
        AY259126
        AY277393
        AY277390
        AY277391
        AK314834
        AY259128
        U72064
        Z83201
        X97291
        DQ179043
        AY054375
        DQ179042
        U41489
        AY504812
        M81174
        AY504813
        AF329281
        AJ297705
        AF306862
        AJ238410
        AJ539471
        M81171
        Y09342
        AY307897
        D89917
        U08275
        U08274
        M30182
        M30181
        AY663397
        U95115
        AB010270
        AM159646
        AF164346
        DQ535034
        AB010269
        AY257483
        AY429728
        AJ515905
        AY429723
        M81180
        AY877348
        X73027
        M57648
        AF093411
        DQ135944
        AJ507780
        AF089719
        AJ297582
        D49468
        AY174184
        AY174181
        AB049832
        AY050186
        AF339884
        AB062112
        DQ140279
        AJ404618
        M20503
        AJ854250
        AF169239
        NM_002125
        U96926
        M17377
        AF052574
        DQ179034
        AF267639
        M17379
        AF142465
        M17384
        AJ507382
        M59798
        M17387
        AF142466
        AF029301
        M17383
        M17382
        M32578
        AY296120
        AY296121
        AY170862
        AJ271159
        EF495154
        U26558
        Y07590
        AF142451
        AJ871009
        S79786
        AJ441130
        AB106129
        AF122887
        AF201762
        X96396
        U17381
        AJ289124
        AJ306404
        545466
        DQ643390
        DQ060439
        D29836
        AJ507425
        AF186408
        AF442519
        AB087875
        AB176444
        AF186407
        Z99006
        U25442
        AY048687
        M15992
        CH878642
        AF142447
        AY305859
        AF142442
        AY664400
        AF142445
        AY664401
        AF450093
        AF234175
        X86803
        AF490771
        U31770
        AF004817
        AJ401148
        BC009234
        AF234181
        AJ488066
        AJ243327
        FN430425
        AF144080
        AM084908
        AY379480
        M35159
        L21755
        AY331806
        AF081676
        AY457037
        AK292140
        AY765349
        L41992
      U11869 DA670033
        U11866
        AK290906
        DQ895671
        NM_001168298
        DA674925
        L19593
        AB032733
        AC124768
        AB032734
        U11873
        U11872
        DQ893661
        AK312664
        M73969
        U11874
        U11875
    Homo sapiens interleukin 8 receptor, beta (IL8RB), mRNA.   AY714242
2900327 IL8RB   AJ710879
        U11876
        U11877
        CH471063
        U11878
        M94582
        BC037961
        M99412
        NM_001557
      AF482762 AF482763
        U91926
        U91927
        AF482766
        AF482767
        BC028208
        AF482764
        AF482765
        NM_006865
        AF025527
        DQ894258
        AF014923
        AF014924
        AF353733
        AC010518
    Homo sapiens leukocyte immunoglobulin-like receptor, subfamily A (without TM domain), member 3 (LILRA3), mRNA.   DQ891075
      CH471135
      AF482769
6110037 LILRA3   AF482768
3180609 LOC100008588 Homo sapiens 18S ribosomal RNA (LOC100008588), noncoding RNA. NT_167214.1
6280504 LOC100008589 Homo sapiens 28S ribosomal RNA (LOC100008589), non-coding RNA. AK225361 NM_033331
        EF611343
        NM_003671
        AF023158
        AF064104
        AL133477
        NM_001077181
        AF064105
        AL353578
        AY675321
        AK126388
        CR601692
        BC156666
        BC050013
        DA943563
        CH471174
        U13369
        NR_003287
        AL592188
6280504 LOC100008589 Homo sapiens 28S ribosomal RNA (LOC100008589), non-coding RNA. NT_167214.1
6420563 LOC100129902 PREDICTED: Homo sapiens similar to mCG7602 (LOC100129902), mRNA. NC_000004.10
650735 LOC100131205 PREDICTED: Homo sapiens hypothetical protein LOC100131205, transcript variant 3 (LOC100131205), mRNA. NR_026911
6650603 LOC100131905 PREDICTED: Homo sapiens misc_RNA (LOC100131905), miscRNA. NC_000012.10
7150414 LOC100132291 PREDICTED: Homo sapiens similar to hCG2027326 (LOC100132291), mRNA. NC_000019.8
4670634 LOC100132394 PREDICTED: Homo sapiens hypothetical protein LOC100132394 (LOC100132394), mRNA. n/a
6580017 LOC100132742 PREDICTED: Homo sapiens hypothetical protein LOC100132742, transcript variant 1 (LOC100132742), mRNA. NC_000001.9
2630347 LOC100134364 PREDICTED: Homo sapiens hypothetical protein LOC100134364 (LOC100134364), mRNA. n/a
3390674 LOC391370 PREDICTED: Homo sapiens similar to hCG1818387 (LOC391370), mRNA. NC_000002.10
3190348 LOC440927 PREDICTED: Homo sapiens similar to 60S acidic ribosomal protein P1, transcript variant 4 (LOC440927), mRNA. n/a
6960373 LOC644191 PREDICTED: Homo sapiens similar to hCG15685, transcript variant 1 (LOC644191), mRNA. NC_000017.9
      AL353735 AC225613
        AC090543
        AC034102
        CH471054
        DQ896038
        CH471057
        AL136526
        BC105798
        AC098847
        AB007161
    PREDICTED: Homo sapiens similar to 40S ribosomal protein S26, transcript variant 1 (LOC644934), mRNA.   AC006463
      U41448
      AC008065
6270307 LOC644934   AB007160
        X69654
        AP004217
        DQ895081
        X79236
        AL138767
        AV681946
        AC126544
        CH236947
        DQ891895
        BC013215
        BC070220
        BC105276
        DQ896089
        AC012391
        DQ892791
        AC027373
        NM_001029
        AC004057
        X77770
        AC025518
        BC015832
        CR611958
        BC002604
1170551 LOC646785 PREDICTED: Homo sapiens misc_RNA (LOC646785), miscRNA. NC_000006.10
6960195 LOC650646 PREDICTED: Homo sapiens similar to 40S ribosomal protein S26 (LOC650646), mRNA. AL445193 CH471059
    Homo sapiens neuroblastoma breakpoint family, member 10 (NBPF10), mRNA. XM_930727_XM_930739 NM_001101663
      BC094705
1510681 NBPF10   AK055895
    XM_930751 XM_930759 XM_930766 XM_930776 XM_930785 XM_930797 XM_930808 XM_930830 XM_930841 XM_930850 XM_930862 XM_930872 XM_930880 XM_930889 XM_930897 XM_930903 XM_930910 XM_930917 XM_930926 XM_930936 XM_930943 XM_930951 XM_930954 XM_930961 XM_930967 XM_930975 XM_930985 XM_930993 XM_931003 XM_931009 XM_931015 XM_931021 XM_931027 XM_931033 XM_931038 XM_931044 XM_931049 XM_931055 XM_931060 XM_931066 XM_931069 XM_931072 XM_931076 XM_931080 XM_931084 XM_931090 XM_931096 XM_931102 XM_931110 XM_931119 XM_931125 XM_931131 XM_931137 XM_931138 XM_931145 XM_931149 XM_931157 XM_931161 XM_931164 XM_931169 XM_931174 XM_931178 XM_931183 XM_931188 XM_931191 XM_931196 XM_931202 XM_931208 XM_931213 XM_931221 XM_931229 XM_931234 XM_931240 XM_931245 XM_931251 XM_931255 XM_931259 XM_931264 XM_931269 XM_931277 XM_931282 XM_931291 XM_931299 XM_931308 XM_931317 XM_931322 XM_931328 XM_931335   AL049742
      AF379606
      AK095030
      AF379607
      BC034418
      CR599564
      XM_002346226
      CR608846
      BC169317
      BC169318
      BC169316
      BC094841
      DB300232
      AF380582
      NM_001037675
      BC086308
      AL117237
      AF380580
      NM_183372
      BC063799
      BX546486
      BC027348
      AL592284
      NM_001039703
      AC026900
      AK302413
      AF379624
      NM_015383
      AF379626
      AF379627
      AF379628
      AK294944
        XM_001726946
        AK092351
        AF379620
        AF379621
        AF379622
        AF379623
        AK054850
        AL359176
        XM_001717398
        AF379615
        AF379616
        AF379613
        AF131738
        AF379614
        AL355149
        AF379619
        AL138796
        BX511041
        AK290302
        AF379617
        AL050141
        AF379618
        BC021111
        AF379611
        AF379612
        AY894574
        BC010124
        AY894573
        BC148331
        AY894572
        AL040349
        AY894571
        AY894570
        BC071995
        AY894579
        AY894578
        AY894577
        AL592307
        AY894576
        AY894575
        AL137798
        AK290142
        AI865471
        AF419617
        XM_001715810
        AF419616
        AF419619
        AF419618
        AK095459
        AF379632
        AY894583
        AF379631
        AL356004
        AY894582
        AF379634
        AY894585
        BC110431
        AF379630
        AY894581
        AK125792
        AY894580
        AL139152
        BC167783
        AK294414
        AF379635
        NM_017940
        AF420437
        BQ890458
        AK000726
        BC136292
        CR600619
        AL954711
        BC071723
        AF161426
        BI552657
        AB051480
        CR610345
        AK097180
        BC023087
        BX648497
        AL022240
        AL832622
        AB033071
        AY894561
        BC013805
        AY894563
        AY894562
        BC066930
        AY894565
        AY894567
        AY894566
        BX538005
        AY894569
        AY894568
        BX842679
        NM_173638
        DQ786323
        AK299360
        NM_001170755
        BC093404
        AK123260
      AL451065 BC048212
        AK094530
        BT007164
        U91512
        BC019336
        AF029251
        CH471089
        U72661
        BC004440
        CR608271
        CR595190
        NM_004148
7380706 NINJ1 Homo sapiens ninjurin 1 (NINJ1), mRNA.   BC000298
      AC096970 AY349131
        CS023558
        BC098110
        CH471055
        NM_021935
        BC069395
        AF333025
        NM_001126128
        BC098162
        BC096695
1030463 PROK2 Homo sapiens prokineticin 2 (PROK2), mRNA.   AF182069
380575 RPL23 Homo sapiens ribosomal protein L23 (RPL23), mRNA. X52839 AC110749
        BC034378
        BC106061
        CR604268
        X55954
        CR610098
        BC104651
        CH471152
        NM_000978
        AB061827
        AL136089
        BC003518
        DQ893218
        CA437923
        BC062716
        DQ896547
        BC010114
        AK024749
      CR618026 CR542152
        BC016748
        L22154
        CH471063
        BC047872
        CR613913
        BC039030
        BC014262
        BC067789
        NM_000998
        L06499
        CD249666
    Homo sapiens ribosomal protein L37a (RPL37A), mRNA.   AC073321
990273 RPL37A   BC063476
        X66699
        BC082239
        AK291857
        BC000555
        AK289472
        D28355
5890730 RPS26L PREDICTED: Homo sapiens 40S ribosomal protein S26-like (RPS26L), misc RNA. AL136526
    Homo sapiens ribosomal protein S26 pseudogene 11 (RPS26P11), non-coding RNA. NR_002309 AL929401
6560376 RPS26P11   AW972305
      AB007164 CH471076
        AU126783
        BC021239
        AC107983
        L05091
        AC005011
        CR606185
        DQ891357
        U58682
        CR603137
        AK293636
        BC070217
        BC070218
        CH471139
        AC010323
        AK301638
        BC018810
        DQ894538
    Homo sapiens ribosomal protein S28 (RPS28), mRNA.   CR457055
650349 RPS28   CH236952
        NM_001031
        AB061846
        BC000354
        AK311925
      X65965 BC035422
        CH471051
        BU164685
        DQ003134
        DQ890587
        Y00472
        X59445
        AK097395
        AM392836
        AY280721
        AK304766
        AY280720
        AY267901
        BT006967
        BU741675
        AY280719
        AY280718
        Y00985
        NM_001024465
        NM_001024466
        BC016934
        CR626136
        AK296809
    Homo sapiens superoxide dismutase 2, mitochondrial (SOD2), nuclear gene encoding mitochondrial protein, transcript variant 2, mRNA.   S77127
      L34157
      X14322
3890326 SOD2   BC001980
        NM_000636
        D83493
        M36693
        AL691784
        X07834
        AK313082
        X15132
        AL050388
        AL135914
        DQ893752
        BC012423
        BG699596
        BM994509
Table 5A: PLSD loading weights for genes from Table 2:
PROBE_IDSYMBOLPLSD Loading weight for Abdominal discomfortPLSD Loading weight for Appendicitis
ILMN_1701603 ALPL 0.29783 -0.29783
ILMN_1761566 C5orf32 -0.25526 0.25526
ILMN_1695157 CA4 -0.01612 0.01612
ILMN_1662524 CXCR1 -0.06819 0.06819
ILMN_2193213 DEFA1 -0.06522 0.06522
ILMN_1679357 DEFA1B 0.04740 -0.04740
ILMN_1725661 DEFA1B -0.01104 0.01104
ILMN_2102721 DEFA1B 0.03026 -0.03026
ILMN_2165289 DEFA3 -0.04788 0.04788
ILMN_1728639 FCGR3B 0.04584 -0.04584
ILMN_1697499 HLA-DRB5 -0.33313 0.33313
ILMN_1680397 IL8RB -0.16264 0.16264
ILMN_1661631 LILRA3 -1.50443 1.50443
ILMN_3243593 LOC100008588 0.33584 -0.33584
ILMN_1733559 LOC100008589 -0.27838 0.27838
ILMN_3256742 LOC100129902 0.17543 -0.17543
ILMN_3214532 LOC100131205 0.57084 -0.57084
ILMN_3275489 LOC100131905 0.42307 -0.42307
ILMN_3275345 LOC100132291 0.01674 -0.01674
ILMN_3249578 LOC100132394 -0.38482 0.38482
ILMN_3202734 LOC100132742 0.14064 -0.14064
ILMN_3246805 LOC100134364 -0.24811 0.24811
ILMN_3293367 LOC391370 0.21413 -0.21413
ILMN_1689712 LOC440927 0.10489 -0.10489
ILMN_3209193 LOC644191 -0.25270 0.25270
ILMN_1678522 LOC644934 -0.09154 0.09154
ILMN_3210538 LOC646785 0.01680 -0.01680
ILMN_1726647 LOC650646 -0.10099 0.10099
ILMN_2155719 NBPF10 0.51417 -0.51417
ILMN_1815086 NINJ1 -0.62920 0.62920
ILMN_1775257 PROK2 0.31264 -0.31265
ILMN_1755115 RPL23 0.42432 -0.42433
ILMN_2051519 RPL37A 0.04629 -0.04629
ILMN_1750636 RPS26L 0.17768 -0.17768
ILMN_2180866 RPS26P11 -0.00077 0.00077
ILMN_1651228 RPS28 0.03448 -0.03448
ILMN_2336781 SOD2 -0.28727 0.28727
Table 5B: PLSD loading weights for genes from Table 3:
PROBE_IDSYMBOLPLSD Loading weight for Abdominal discomfortPLSD Loading weight for Appendicitis
ILMN_1701603 ALPL 0.30 -0.30
ILMN_1761566 C5orf32 -0.26 0.26
ILMN_1697499 HLA-DRB5 -0.33 0.33
ILMN_1680397 IL8RB -0.16 0.16
ILMN_1661631 LILRA3 -1.50 1.50
ILMN_3243593 LOC100008588 0.34 -0.34
ILMN_1733559 LOC100008589 -0.28 0.28
ILMN_3249578 LOC100132394 -0.38 0.38
ILMN_3246805 LOC100134364 -0.25 0.25
ILMN_3293367 LOC391370 0.21 -0.21
ILMN_3209193 LOC644191 -0.25 0.25
ILMN_2155719 NBPF10 0.51 -0.51
ILMN_1815086 NINJ1 -0.63 0.63
ILMN_1775257 PROK2 0.31 -0.31
ILMN_1755115 RPL23 0.42 -0.42
ILMN_2336781 SOD2 -0.29 0.29

Functional analysis of DEG transcripts.



[0071] Of the well annotated transcripts, several had prior published relationships to infection, immunity, or inflammation, or stress/injury: notably, alkaline phosphatase liver/bone/kidney isoform (ALPL), carbonic anhydrase IV (CA4), chemokine (C-X-C motif) receptor 1 (CXCR1), defensin α1 (DEFA1), defensin α3 (DEFA3), IgG Fc receptor IIb (FCGR3B/CD16B), interleukin 8 receptor β (IL8RB), ninjurin 1, (NINJ1), prokinectin 2 (PROK2), and superoxide dismutase 2 (SOD2). In addition to their logical connection to appendicitis, which often has an infectious etiology, certain aspects of this expression pattern increase the confidence that some of these changes are non-random: 1) multiple probe sets identifying the same transcript (DEFA1), 2) 'hits' on highly related transcripts, such as DEFA1 and DEFA3, as well as CXCR1 (aka IL8 receptor β) and IL8 receptor β.

[0072] Defensins. To understand the defensin pathway, the 5 α-defensin transcripts in the DEG list, which are all variant transcripts from the DEFA locus at 8p21.3, were averaged to create a 'defensin score', and then compared between groups (Table 1). Using a threshold determined by the mean of all 20 patients (1.87), 6 of 9 (67%) patients with other abdominal disorders showed elevated defensins, while only 1 of 11 (9%) of appendicitis patients had elevated defensin mRNA (see defensin cluster in Figure 2). Surprisingly, the defensin score was essentially uncorrelated with white blood cell count (WBC) (r = 0.07) and neutrophil % (r = 0.15).

[0073] Other immune/inflammatory pathways. Interestingly, 3 of the 37 DEG (LILRA3, CXCR1/IL8RA, FCGR3A), which were higher in appendicitis patients compared to abdominal pain patients, are near or exact matches to transcripts discovered previously as downregulated by exposure of isolated human neutrophils to E. Coli [18]. However, across the 20 patients, they were not inversely correlated with defensin expression (LILRA=0.02, CXCR1=-0.02, FCGR3A=-0.33), suggesting they are regulated independently of infectious markers. Other transcripts were readily associated with tissue injury or inflammation, but not previously associated with pathogen infection. For instance, NINJ1 was identified as a transcript strongly upregulated after peripheral nerve injury [19]. PROK2 is elevated in colitis tissue [20], which, like appendicitis, is an inflammatory condition in the GI tract. Likewise, ALPL has a well-known role in modulating diverse inflammatory conditions not limited to infectious disease [21].

[0074] Ribosomal transcripts. While it is widely assumed that ribosomal RNAs (rRNA), such as 18S and 28S non-coding RNAs are 'invariant', or 'housekeeping' transcripts, there is considerable evidence that they are carefully regulated in cases such as granulocyte activation [22], and differ significantly in prostate cancer [23], and in hepatitis C infected livers [24]. In fact, early studies with PHA-activated human lymphocytes demonstrated as much as 8-fold increases in rRNA levels within 20 hours [25,26]. Furthermore, if the observed changes were due to some type of loading or processing anomaly, then we would expect all of the ribosomal RNAs to be affected in the same direction, when in fact, 18S and 28S noncoding transcripts were increased in appendicitis, but most of the transcripts coding for ribosomal proteins were decreased, suggesting that this is a regulated process.

[0075] Minimally annotated transcripts. Of the 37 DEG, 11 transcripts were minimally annotated, i.e. 'predicted transcript', but further manual annotation using NCBI Gene revealed high likelihood assignments. Remarkably, 8 of the 11 transcripts were identified as ribosomal protein pseudogenes, which is quite unlikely to have occurred by chance. Two transcripts have been discontinued, and the eleventh was identified as CYSTM1 (C5ORF32), which is a cysteine-rich transmembrane module-containing protein that 2-hybrid screens identified as an inhibitor of the glucagon-like peptide 1 receptor (GLP-1R) [27].

Prediction of appendicitis from DEG.



[0076] The PLSD model built on the 37 DEG list, was 100% accurate and specific within the discovery set, which is not surprising given the ability of PLSD models to accurately 'fit' data to outcomes. As shown in Figure 3, the first 3 latent factors in the PLSD model demonstrate tight clustering of the appendicitis patients (▲) distinct from patients presenting with other abdominal pain (■). Clearly, 7 of 9 abdominal patients can be discriminated by only the first latent factor (t0, X-axis). Two abdominal patients, one with a GI bleed and one with diverticulitis, are poorly discriminated by the t0 latent factor shown in the X-axis, but are readily discriminated by one of the two other factors (Y or Z axis). To determine whether all 37 transcripts were necessary for prediction, 16 transcripts with a loading of >0.2 in the PLSD model were used to rebuild a new PLSD prediction model (Table 3, above). This smaller model, which omitted the defensins, remained quite strong, predicting 100% of abdominal cases, 90.9% of appendicitis cases, for an overall accuracy of 95%.

[0077] Based on these data, a highly predictive model can be generated by observing expression level patterns utilizing as few as 3 RNA transcripts. Of course the more levels that are measured, the more sensitive and predictive the patterns become. Accordingly, the present invention can use the pattern generated from 3 or more RNA transcripts, 4 or more RNA transcripts, 5 or more RNA transcripts, 6 or more RNA transcripts, 7 or more RNA transcripts, 8 or more RNA transcripts, 9 or more RNA transcripts, 10 or more RNA transcripts, 12 or more RNA transcripts, 14 or more RNA transcripts, or 16 or more RNA transcripts. The only minimum is that the number and selection of transcripts define a pattern that distinguishes appendicitis from other causes of abdominal pain. In embodiments, the method is at least 75% accurate, for example at least 80% accurate, at least 90% accurate, or at least 95% accurate.

[0078] Figure 3 shows a graph displaying the Partial Least Squares Discriminant (PLSD) Model for classification of appendicitis from RNA biomarkers. In Figure 3, DEGs were analyzed by PLSD to compose a classification model for appendicitis based on RNA biomarkers in blood. The 3D plot shows the 20 patients in the discovery set as partitioned by the first 3 of 4 latent factors in the PLSD model. The ■ represent abdominal pain patients (n=9), and ▲ shows the cluster of appendicitis patients (n=11), as a function of the t0 latent factor (X-axis), the t1 factor (Y-axis), and the t2 factor (Z-axis). The majority of patients (7/9) are accurately classified by the t0 component alone.

Validation of PLSD prediction model in unrelated samples.



[0079] To determine the robustness of the prediction model, a separate group of patients derived from the same overall cohort were similarly processed for whole blood RNA, and hybridized independently to Illumina HT 12v4 Beadchip arrays. With only minimal normalization to correct for minor loading and hybridization differences, the PLSD prediction model was applied to the normalized values for the 37 transcripts in the model. The PLSD prediction model correctly identified 8 of 9 true appendicitis patients (88.9%) and predicted 3 of 4 patients (75%) with hernias as being 'abdominal pain'. Nearly 90% sensitivity in an unrelated cohort quantified on a different microarray run is encouraging toward the potential robustness of the model. Notably, the PLSD model includes no clinical variables, such as fever or white cell count.

Behavior of the RNA biomarkers in non-appendicitis infections.



[0080] In 5 patients clinically diagnosed with LRI, which were not included in PLSD training, the model predicts 4 of 5 as appendicitis (80%), suggesting that the model may be sensitive to generalized infectious or inflammatory signals in blood. Using the 16 DEG model, only 60% were diagnosed as appendicitis. As shown in Figure 5, some transcripts, such as FCGR3 and NINJ1, were relatively selectively elevated in APP, but not LRI. Other transcripts, especially defensins, were much more sensitive to LRI than APP, showing 4-5 fold elevations in LRI versus HER, and 20-fold elevations in LRI vs APP. Most transcripts, as demonstrated by IL8Rβ, LILRA3, and ALPL, showed roughly similar changes in LRI and APP. Of the 37 transcripts, 10 are relatively selective for APP, 8 are selective for LRI, and 19 behave similarly in both APP and LRI.

[0081] Figure 5 shows graphs displaying the behavior of DEG biomarkers in a validation cohort. In Figure 5, the 37 DEG biomarker set was applied to transcript expression levels in unrelated patients presenting at the ER for either appendicitis (APP, green bars), lower respiratory infection (LRI, red bars), or hernias (HER, blue bars). Representative transcripts, such as Fc gamma receptor 3 (FCGR3) and ninjurin 1 (NINJ1) are shown, in which the transcript behaves with relatively selective induction in APP, relative to HER or LRI. Conversely, transcripts in the defensin family (DEFA1, DEFA3), are significantly elevated in HER patients, relative to APP, but are strikingly induced in LRI patients. Most transcripts, such as alkaline phosphatase (ALPL) and the IL8 receptors (IL8RB, CXCR1), were induced in both APP and LRI patients.

DISCUSSION



[0082] Currently, there are no FDA-approved serum or urine biomarkers for abdominal pain or appendicitis. As noted earlier, abdominal pain is one of the most common complaints in the ED, and thus blood biomarkers represent an important unmet need in clinical medicine. In this discovery and validation study, we have identified a small set of RNA transcripts associated with appendicitis. Overall, a prediction model built on these markers was able to differentiate appendicitis from other forms of intra-abdominal pathology, such as diverticulitis and hernias. Appendicitis is thought to be an inflammatory disease, similar to diverticulitis or colitis; however, there was differing activation of certain mRNA biomarkers between these conditions. Furthermore, the 37 DEG markers do not correlate with white blood cell count, per se, but a careful examination of the transcripts suggests that the RNA biomarkers may be measuring the activation state of immune cells, especially neutrophils.

[0083] The pattern of transcriptome changes in blood may help to refine our understanding of the etiology and progression of acute appendicitis, as shown schematically in Figure 6. The classic explanation for appendicitis is that a fecalith or lymphoid hyperplasia block the outflow of the appendix, resulting in obstruction and ischemia [28]. Outflow obstruction may produce local changes that favor undesirable changes in the appendix microbiome. Several recent studies, including next-generation sequencing (NGS) of the 16S regions of the microbiome, have suggested that relatively selective changes in fusobacteria species are associated with appendicitis [29-32]. Fusobacteria, a type of gram-negative bacteria, can induce toxicity in adjacent host cells, and colitis-like symptoms in mice, potentially by producing butyric acid (butyrate) [33]. RT-PCR analysis confirms that inflamed appendix tissue has elevated α-defensin and IL-8 mRNA levels [34]. Likewise, fusobacterium nucleatum biofilms stimulate IL-8 production in human oral epithelium cell lines [35] and fusobacterium necrophorum induces IL-8 production in cultured mesothelial cells [36].

[0084] Figure 6 shows a schematic of a model of appendicitis biomarker pathophysiology. It is believed that compacted fecal bodies, termed fecaliths, may occlude the outflow tract of the appendix, causing inflammatory conditions that are conducive to infection in the appendix. Microbiome analysis of inflamed appendices typically indicates a predominance of biofilm-forming bacteria, such as fusobacteria. The biofilm protects the bacteria from antibiotics, and from direct immune attack, but soluble factors produced by the bacteria, such as LPS (endotoxins) and butyrate, or IL-8, can diffuse into adjacent lymphatic and circulatory beds to activate neutrophils. The primed neutrophils respond with elevated transcript levels of alkaline phosphatase (ALPL), interleukin-8 receptor beta (IL8Rβ) and related biomarkers of local infection. Background images of appendix and neutrophil courtesy of Blausen.com staff, Wikiversity Journal of Medicine.

[0085] Thus, the absence of elevated α-defensin transcripts in the presence of elevated levels of mRNA for both IL-8 receptors suggests that circulating immune cells are primed by IL-8 produced in the inflamed appendix. However, it seems likely that the immune cells are not directly contacting the bacterial infection, which would elevate defensins, as demonstrated clearly in the LRI patients.

[0086] In addition to the IL-8 receptors, several other transcripts appear to be plausible biomarkers of localized inflammation. Notably, ALPL, along with IL8RB/CXCR2, was identified as an expression biomarker of asthma inflammatory subtypes [37]. In addition to these interesting innate immune markers, the results revealed unexpected changes in the ribosomal system. Humans utilize 4 ribosomal RNAs, which are non-coding (5S, 5.8S, 18S, 28S), and ∼80 ribosomal proteins to build multimeric translation complexes. Additionally, there are ∼2000 ribosomal protein pseudogenes, which are thought to derive from inactivated duplications, but may be processed to varying degrees, and could have regulatory functions [38]. Transcripts for 18S and 28S, both originating from multiple 45S genes, were increased in the appendicitis blood RNA, which could be due to both increased transcription from active rDNA genes [39], as well engagement of previously inactive rDNA transcription units [26]. Conversely, most of the coding transcripts, such as RPLP1 and RPS26, were decreased in the blood of appendicitis patients. Because the specific pattern of ribosomal proteins defines the type of RNAs that are engaged and translated [40], it is possible that the translational machinery is being re-geared to adapt to a new demand. Unexpectedly, most of the poorly annotated transcripts mapped to ribosomal protein pseudogenes, suggesting that either the probesets are incorrectly detecting a change in coding ribosomal protein transcripts, or the pseudogenes are somehow regulated in conjunction with the reconfigured translational machinery. Conceptually, the pattern of chemokine, defensin, stress-related, and ribosomal processing changes is consistent with the immune system being 'primed' as the immune cells pass through an inflammatory field created by a localized biofilm infection.

[0087] Other investigators have sought to develop protein biomarkers for appendicitis in the blood, such as bilirubin [41], C-reactive protein (CRP) [42], and pro-calcitonin (PCT) [43]. However, recent comparisons of these biomarkers had difficulty improving on a purely clinical prediction model, such as the Alvarado score (ROC=0.74, vs CRP=0.61, PCT=0.69) [44]. Recently, a combination of WBC, CRP, and MRP8/14 (S100A8/S100A9) was shown to be 96% sensitive, but 43% specific for acute appendicitis [42]. Likewise, a multivariate model built on plasma protein levels of serum amyloid (SAA), myeloperoxidase (MPO), and MMP9 was less diagnostic than a largely clinical model (ROC = 0.71 vs 0.91 clinical model) [45].

[0088] While RNA-based diagnostic tests are currently on the market for breast cancer progression (MammaPrint, OncoType Dx), transplant rejection (AlloMap), and coronary artery disease (CorusCAD), this is the first report to assess blood RNA as a potential biomarker of appendicitis. Among the strengths of the present approach is that the test and validation sets included controls for surgical, inflammatory, and infectious factors. Further, the RNA profiling was broad and largely unbiased, and detected the same key pathways in the test and validation study.

[0089] Genome-wide RNA transcript profiling is thus demonstrated as being capable of identifying biomarkers of appendicitis. The detected biomarkers are consistent with prior published evidence that fusobacteria biofilms in the appendix may be an important putative mechanism in appendicitis.

[0090] By assaying the RNA levels by microarray analysis, alternative methods of assaying RNA levels can be applied in the steps of this invention. Examples of alternative methods including are real-time RT-PCR, real-time PCR, quantitative RT-PCR, qPCR, RT-PCR array, RNA sequencing (RNA-Seq), northern blot, and serial analysis of gene expression (SAGE), measuring protein expression.

[0091] Patterns of RNA levels define biomarkers that identify appendicitis. Differential expression of RNA levels of a gene often coincide with differential expression levels of the resultant proteins translated from the RNA. For this reason, measuring the protein expression level patterns that correlate to the identified differentially expressed genes is an alternative method of diagnosing appendicitis. Protein expression levels can be measured from serum samples by a number of means including western blot, enzyme-linked immunosorbent assay (ELISA), mass spectrometry, and other means that utilize antibody detection of proteins. Similar methods of testing as described for the RNA biomarkers can be used by replacing RNA measurement with protein measurement and determining suitable patterns. According to his embodiment, measuring the protein expression level patterns will diagnose appendicitis. In some embodiments, antibodies against specific proteins can be generated and used to measure protein expression levels.

References for Background and Example 1:



[0092] 
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Example 2: Confirmation of microarray results



[0093] Quantitative Real Time Polymerase Chain Reaction (Q-RTPCR) was sued to confirm the microarray results from Examples 1 and 2. Figure 7 shows Q-RTPCR results for 3 genes: ALPL, DEFA1/3 and IL8RB. As seen in Figure 7, results obtained from Q-RTPCR parallel the results obtained from the microarray assays.

Methods


1) RNA purification:



[0094] 1.1) For validation studies, the RNA purified for microarray analysis was used. In new samples, or other embodiments, the sample of blood must be collected in an appropriate RNA stabilizer. In the present studies, Tempus tubes were used. Other stabilizers could be used, but it is possible that the specific transcripts levels of expression or their magnitude, could be different depending upon the RNA Blood tubes used and their RNA stabilizers. From the Tempus tubes, the manufacturer's instruction and reagents for column purification of RNA was used. However, technically, both DNA and RNA are purified.

2) DNAse treatment:



[0095] 

2.1) To remove the DNA, which will confuse the quantitation of RNA, the sample is treated with Turbo DNA-Free™ Kit (ThermoFisher Sci, Cat. No AM1907). We used up to 5 ug total RNA/DNA treated with 2 units/µL of TurboDNAse for 30 min at 37°C. The inactivation of DNAse was performed using the "Inactivation Reagent" (IR) provided in the kit at 0.2 X volume of the total reaction, typically 20 µL of IR for 100 µL of DNase treatment. The IR contains an affinity capture reagent recognizing the TurboDNAse, thereby removing it from solution, and eluting relatively pure RNA. A variety of DNAse removal strategies are well known to anyone skilled in the art. In particular, it is common to heat-inactivate the DNAse. While probably acceptable, it has not been specifically tested, and we cannot exclude the possibility that this would be a source of variation (SOV).

2.2) The DNase treated RNA is further purified in Qiagen RNAeasy MiniElute kit (Qiagen, Cat. No. 74204) on columns The RNA quantity is assessed by absorbance at 260 nm (NanoDrop) and the quality is assessed by the ratio of absorbance at 260 nm (RNA) to 280 nm (protein). A ratio (260/280) greater than 1.8 is desirable if measured in water, and greater than 2.0 if measured in water buffered with Tris/EDTA (TE).


3) Complementary DNA (cDNA) Synthesis:



[0096] 3.1) The purified RNA was converted to cDNA using reverse transcriptase (RT) contained in the iScript cDNA Synthesis kit from Bio-Rad Laboratories (Cat. No. 170-8891). There are published reasons to believe that the type of RT enzyme could affect the efficiency of cDNA synthesis, and therefore, the measured levels of specific transcripts by qRT-PCR. In particular, the presence or absence of the RNAse H activity in the RT enzyme might be a relevant SOV. The iScript cDNA kit reverse transcriptase contains RNase H enzymes for degradation of RNA template in the amplification process.

4) PCR Probe selection:



[0097] 

4.1) Sense and antisense probes for PCR were selected using the cDNA sequences extracted from Genbank accession numbers disclosed in Table 1. The cDNA sequences were analyzed by Geneious software to identify primers with matching melting temperatures (Tm) of 60°C under standard RT-PCR conditions. The primers identified and used are shown in Table 1.

4.2) In this example, 6 transcripts were targeted for qRT-PCR quantitation. Four of these transcripts (ALPL, DEFA1, DEFA3, IL8RB) were selected from the 16g and 37g lists of DEGs that are diagnostic of appendicitis. Two other transcripts, ACTB and SpiB, were used as transcripts which should not vary according to appendicitis status, and thus are considered 'invariant' for this example.

4.3) For each transcript-specific reaction, additional samples are prepared in which the pooled control cDNA (Con) is used at higher, and lower quantities, typically in 10-fold steps, to create a standard dose-response curve for each primer pair. This curve confirms that the qPCR is able to detect higher and lower transcript levels, and is used to convert the Ct to a relative abundance measure as described below.


5) qRT-PCR conditions:



[0098] 

5.1) A standard amount of cDNA (0.20-0.25 ng) from the patient samples, or a pooled control sample (Con), was combined with a fixed amount of the transcript-specific primer pairs (1.25 µM) and a master mix SSO Advanced™ Universal SYBR® Green Supermix (Bio-Rad, Cat. No.: 172-5274) containing a mix of antibody-mediated hot-start Sso7d fusion polymerase, dNTPs, MgCl2, enhancers, stabilizers, a blend of passive reference dyes (including ROX and fluorescein) and SYBR Green fluorescent dye, which reports the level of PCR amplimer that is present after each amplification cycle. There are numerous acceptable ways to quantitate PCR amplimer levels, including, but not limited to, SYBR Green, EVA green, and fluorescently-labeled internal probes commonly referred to TaqMan probes. Another envisioned embodiment of the invention would be to quantitate the transcript levels using droplet digital PCR (ddPCR, BioRad) or hybrid-based transcript counting methods, such as Nanostring.
In this example, we employed the BioRad SSOAdvanced kit reagents. Each transcript-specific primer pair and sample, cDNA was analyzed in a separate well of a 384-well plate in duplicate for each primer pair. Thus, for a given patient sample, 12 qPCR reactions were performed (6 primer pairs, each in duplicate). The mixture containing probes, cDNA sample, and PCR reagents, including fluorescent dye, in a final volume of 14 µl, were loaded using the automatic liquid handler (Eppendorf, epMotion® 5770) subjected to thermocycling as described below.

5.2) The mixture of these reagents was incubated in a BioRad CFX384™ Real-Time System with C1000™ thermocycler using a temperature program of: 2 min at 98°C, followed by 45 amplification cycles of 5 sec at 98°C, and 10 sec @ 60°C, finalized with 10 sec @ 75°C and 4 sec @ 95°C dissociation stage. After each cycle, the level of fluorescence of the SYBR Green dye bound to dsDNA amplimers was quantified by stimulation with appropriate filters for excitation and emission. The reaction was cycled 40 times and then held at 4°C after the last cycle.


6) Data analysis:



[0099] 

6.1) The real-time quantitative PCR instruments measure fluorescence generated by the amplimer/dye complex after each cycle of amplification. Because the amounts of primers and free nucleic acids are limiting, these reaction reach a saturated maximum of fluorescence typically prior to 40 cycles of amplification. The number of cycles observed to reach half-maximal fluorescent intensity is said to be a Cycle Threshold (Ct) of Cycle Quantity (Cq) which is inversely correlated to the amount of transcript cDNA in the reaction. Thus, the higher the level of target cDNA present, the fewer cycles will be needed to reach a given Ct. In practice, there are numerous acceptable methods to stipulate the Ct based on the fluorescence curve, and as long as the Ct is applied uniformly to the samples in each transcript-specific reaction, including the Con samples, then the results should be informative for the present purposes.

6.2) The Ct values for each reaction are converted to a relative abundance (RA) of the transcript by interpolation to the standard curve for each primer pair. That RA level per duplicate PCR tube is then averaged for the 2 duplicates, and then adjusted by the abundance of the 'invariant' transcript levels. A very large number of invariant transcripts would be acceptable, and some that are commonly used by those skilled in the art include: glyceraldehyde 3-phosphate dehydrogenase (GAPDH), β-actin (ACTB), hypozanthine phosphoribosyltransferase 1 (HPRT), and 18S ribosomal RNA. In the present invention, it was empirically determined that ACTB provided efficient normalization, but the invention is not constrained by the method of normalization.

6.3) The RA levels of the 4 diagnostic transcripts were combined in the following way to predict the outcome of appendicitis:

6.3.1) To account for arbitrary nature of RA value, it was normalized to a percentile of the mean value in the entire run of 36 samples, yielding a %RA value, where 1.00 would be equal to the mean value of that transcript target.

6.3.2) Using the %RA value, the diagnostic goal is to determine whether the ALPL and IL8RB levels are increased disproportionately to the DEFA1 levels. In principle, DEFA3 levels could be used, or a combination of DEFA1 and DEFA3 levels, but for simplicity DEFA1 levels were found to be adequate. Thus, the ratio of %RA of ALPL (%ALPL) to %RA of DEFA1 (%DEFA1), and the ratio of %RA of IL8RB (%IL8RB) to %DEFA1 were computed to yield %ALPL/%DEFA1 and %IL8RB/%DEFA1. Those two values were averaged to compute the App Score. In this series of 36 patient samples, the App Score had a range of 0.04-44.7.



[0100] Thus, to summarize,



6.3.3) On both logical grounds, and empirical observation, if the App Score is >1 then the normalized ALPL and IL8RB levels are higher than DEFA1 levels and this is taken as diagnostic of an increased likelihood of appendicitis. In actual practice, there would be numerous mathematical and technical means to arrive at a similar assessment of the relative levels of these predictive transcripts identified in the 16g or 37g lists.

6.3.4) To test the diagnostic ability of the App Score, it was converted to a scale of 1-10 which is a common metric range used in the Receiver-Operator Characteristic (ROC) statistic. The conversion from App Score to App Level (1-10) was achieved with the following conversion table:

Table 6: Conversion Table for converting App Score to App Level
Coding Key 
App ScoreApp Level
<0.2 1
<0.4 2
<0.6 3
<0.8 4
<1.0 5
<2 6
<4 7
<8 8
<16 9
>16 10


[0101] As discussed above, a predictive test was built taking the data from Figure 7. A very simple way to predict Appendicitis (Appy) using only 3 gene transcripts (IL8RB, DEFA1, ALPL) and one control transcript (Actin) was developed. Figure 8 shows a graph of the ROC curve with sensitivity and specificity. In practice, the test gives a score from 1 to 10, where 5-6 is about a 50% risk of Appy, and a score above 7 indicates likely Appy.

[0102] The true presence or absence of appendicitis was known from clinical analysis and was scored as a binary variable where 0=absent, 1=appendicitis. Five of the 36 patients were excluded from analysis because they had a clinical diagnoses of lower respiratory infection, which is unrelated to the present invention. An App Score >1, which is an App Level of 6 or greater, was used as a threshold for predicted appendicitis. The predicted outcome (App Level) and the true outcome were used to compute a 'confusion table' and an ROC curve by the method of John Eng: (JROCFIT: Johns Hopkins University, Baltimore, MD Version 1.0.2, March 2004. URL: http://www.rad.jhmi.edu/jeng/javarad/roc/JROCFITi.html).

[0103] The results are shown in Figure 8, and indicate that overall the accuracy was 80.6%, with 94.4% sensitivity in detecting clinically diagnosed appendicitis.

Example 3: Prediction of appendicitis from blood and urine samples



[0104] Blood and urine samples were collected from emergency department patients with abdominal pain.

[0105] Analyte concentrations in plasma and urine samples were measured by immunoassay with commercially available reagents using standard sandwich enzyme immunoassay techniques. A first antibody which binds the analyte is immobilized in wells of a 96 well polystyrene microplate. Analyte standards and test samples are pipetted into the appropriate wells and any analyte present is bound by the immobilized antibody. After washing away any unbound substances, a biotinylated second antibody which binds the analyte is added to the wells, thereby forming sandwich complexes with the analyte (if present) and the first antibody. Following a wash to remove any unbound biotinylated antibody reagent, streptavidin-conjugated horseradish peroxidase is added to the wells. Following another wash, a substrate solution comprising tetramethylbenzidine and hydrogen peroxide is added to the wells. Color develops in proportion to the amount of analyte present in the sample. The color development is stopped and the intensity of the color is measured at 450 nm and 540 nm or 570 nm. An analyte concentration is assigned to the test sample by comparison to a standard curve determined from the analyte standards. Units for all analytes reported herein are ng/mL.

[0106] Patients with abdominal pain were determined to have appendicitis (Appy) or not have appendicitis (ABD) by physician diagnosis based in part on a computerized tomography (CT) scan. Protein concentrations in the "Appy" and "ABD" cohorts are compared using the Wilcoxon-Mann-Whitney test. The ability of a protein biomarker to distinguish between the "Appy" and "ABD" patients is determined using receiver operating characteristic (ROC) analysis.
Table 7.1 Protein Concentrations in Plasma. P-values for Wilcoxon-Mann-Whitney test are reported.
 ALPLCA4DEFA1DEFA3FCGR3BLILRA3
 ABDAppyABDAppyABDAppyABDAppyABDAppyABDAppy
5th percentile 99.5 87.9 8.5 5.9 7.7 8.3 5.6 6.5 0.00 0.00 0.00 0.00
25th percentile 114.7 116.9 14.5 11.0 9.1 9.5 7.5 6.8 0.00 0.00 0.00 0.00
Median 171.2 146.1 27.5 21.0 12.2 11.4 9.1 7.1 0.00 0.00 0.53 0.00
75th percentile 240.5 176.8 59.4 27.1 16.2 13.6 13.2 8.4 0.44 0.34 1.76 0.93
95th percentile 548.4 471.6 109.5 108.1 22.9 100.4 59.1 11.1 3.49 2.43 3.78 2.75
P 0.270 0.180 0.606 0.018 0.803 0.205
Table 7.2 Protein Concentrations in Urine. P-values for Wilcoxon-Mann-Whitney test are reported.
 ALPLCA4DEFA1DEFA3FCGR3BLILRA3
 ABDAppyABDAppyABDAppyABDAppyABDAppyABDAppy
5th percentile 0.0 0.0 0.00 0.00 0.0 1.7 0.0 0.0 0.00 0.00 0.00 0.00
25th percentile 0.3 0.0 0.00 0.00 2.9 4.8 0.4 0.0 0.00 0.00 0.00 0.00
Median 2.6 1.9 0.00 0.00 10.8 10.6 1.1 0.3 0.02 0.00 0.00 0.00
75th percentile 7.7 4.5 0.30 0.52 33.2 13.4 3.9 1.0 2.69 0.08 0.35 0.00
95th percentile 63.4 7.9 1.31 0.70 809.1 24.9 25.9 2.4 25.82 0.39 3.34 0.37
P 0.047 0.295 0.065 0.034 0.230 0.691
Table 8.1 Area under the receiver operating characteristic curve (AUC) of proteins in plasma. An AUC < 0.5 indicates protein concentrations are generally lower in patients with appendicitis. P-values for the null hypothesis of AUC = 0.5 are reported.
AssayUniprot #AUCSEABD (no appendicitis)Appendicitisp
DEFA3 P59666 0.291 0.095 45 11 0.027
CA4 P22748 0.369 0.099 45 11 0.183
LILRA3 Q8N6C8 0.376 0.099 45 11 0.209
ALPL P05186 0.396 0.099 45 11 0.295
DEFA1 P59665 0.462 0.099 45 11 0.698
FCGR3B 075015 0.492 0.098 45 11 0.934
Table 8.2 Area under the receiver operating characteristic curve (AUC) of proteins in urine. An AUC < 0.5 indicates protein concentrations are generally lower in patients with appendicitis. P-values for the null hypothesis of AUC = 0.5 are reported.
AssayUniprot #AUCSEABD (no appendicitis)AppendicitisP
DEFA3 P59666 0.293 0.095 45 11 0.029
ALPL P05186 0.307 0.096 45 11 0.044
DEFA1 P59665 0.319 0.097 45 11 0.061
FCGR3B 075015 0.393 0.099 45 11 0.281
CA4 P22748 0.404 0.099 45 11 0.334
LILRA3 Q8N6C8 0.534 0.099 45 11 0.729
Table 9.1. Confusion table and odds ratio for appendicitis using plasma DEFA3. A cutoff concentration of 122 ng/mL is selected corresponding to the 33rd percentile.
 Adjudication 
DEFA3ABDAppyTotal
<= cutoff 11 8 19
> cutoff 34 3 37
Total 45 11 56


[0107] Odds ratio (95% CI) = 8.2 (1.9 - 34.2), where Odds ratio = Odds below cutoff / Odds above cutoff.
Table 9.2. Confusion table and odds ratio for appendicitis using urine ALPL. A cutoff concentration of 2.47 ng/mL is selected corresponding to the 50th percentile.
 Adjudication 
ALPLABDAppyTotal
<= cutoff 19 9 28
> cutoff 26 2 28
Total 45 11 56


[0108] Odds ratio (95% CI) = 6.2 (1.3 - 28.3), where Odds ratio = Odds below cutoff / Odds above cutoff.
Table 9.3. Confusion table and odds ratio for appendicitis using urine DEFA1. A cutoff concentration of 10.85 ng/mL is selected corresponding to the 50th percentile.
 Adjudication 
DEFA1ABDAppyTotal
<= cutoff 19 9 28
> cutoff 26 2 28
Total 45 11 56


[0109] Odds ratio (95% CI) = 6.2 (1.3 - 28.3), where Odds ratio = Odds below cutoff / Odds above cutoff.
Table 9.4. Confusion table and odds ratio for appendicitis using urine DEFA3. A cutoff concentration of 0.33 ng/mL is selected corresponding to the 25th percentile.
 Adjudication 
DEFA3ABDAppyTotal
<= cutoff 8 7 15
> cutoff 37 4 41
Total 45 11 56


[0110] Odds ratio (95% CI) = 8.1 (2.0 - 33.1), where Odds ratio = Odds below cutoff / Odds above cutoff.

[0111] The individual biomarker assay results obtained from each sample were combined to provide a single result as indicated herein, and the single result treated as an individual biomarker using standard statistical methods. In expressing these combinations, the arithmetic operators such as "x" (multiplication) and "/" (division) are used in their ordinary mathematical sense.
Table 10.1. AUC of combinations of 2 plasma proteins. An AUC < 0.5 indicates protein concentrations are generally lower in patients with appendicitis. P-values for the null hypothesis of AUC = 0.5 are reported.
2-Marker CombinationAUCSENDDp
ALPL x DEFA3 0.285 0.094 45 11 0.0224
DEFA3 x LILRA3 0.285 0.094 45 11 0.0224
CA4 x DEFA3 0.319 0.097 45 11 0.0612
CA4 x LILRA3 0.323 0.097 45 11 0.0678
ALPL x CA4 0.331 0.097 45 11 0.0827
Table 10.2. AUC of combinations of 2 urine proteins. An AUC < 0.5 indicates protein concentrations are generally lower in patients with appendicitis. P-values for the null hypothesis of AUC = 0.5 are reported.
2-Marker CombinationAUCSENDDp
ALPL x DEFA1 0.271 0.093 45 11 0.0137
ALPL x FCGR3B 0.281 0.094 45 11 0.0195
DEFA1 x DEFA3 0.281 0.094 45 11 0.0195
ALPL x DEFA3 0.288 0.094 45 11 0.0247
CA4 x DEFA1 0.293 0.095 45 11 0.0290
CA4 x DEFA3 0.294 0.095 45 11 0.0299
LILRA3 / DEFA3 0.705 0.095 45 11 0.0309
LILRA3 / ALPL 0.701 0.095 45 11 0.0349
DEFA3 x FCGR3B 0.307 0.096 45 11 0.0441
ALPL x CA4 0.308 0.096 45 11 0.0453
CA4 x FCGR3B 0.323 0.097 45 11 0.0678
Table 10.3. AUC of combinations of 1 urine (u) and 1 plasma (p) protein. An AUC < 0.5 indicates protein concentrations are generally lower in patients with appendicitis. P-values for the null hypothesis of AUC = 0.5 are reported.
2-Marker CombinationAUCSENDDp
DEFA1(u) x LILRA3(p) 0.246 0.091 45 11 0.0051
DEFA1(u) x CA4(p) 0.271 0.093 45 11 0.0137
ALPL(u) x DEFA3(p) 0.277 0.094 45 11 0.0170
DEFA3(u) x DEFA3(p) 0.279 0.094 45 11 0.0182
DEFA3(u) x LILRA3(p) 0.280 0.094 45 11 0.0189
DEFA1(u) x DEFA3(p) 0.289 0.095 45 11 0.0255
DEFA3(u) x ALPL(p) 0.291 0.095 45 11 0.0272
DEFA3(u) x CA4(p) 0.299 0.095 45 11 0.0349
DEFA1(u) x ALPL(p) 0.299 0.095 45 11 0.0349
FCGR3B(u) x DEFA3(p) 0.309 0.096 45 11 0.0466
ALPL(u) x LILRA3(p) 0.310 0.096 45 11 0.0479
FCGR3B(u) x LILRA3(p) 0.316 0.096 45 11 0.0565
ALPL(u) x ALPL(p) 0.317 0.096 45 11 0.0580
DEFA1(u) x DEFA1(p) 0.333 0.097 45 11 0.0868
DEFA3(u) x DEFA1(p) 0.333 0.097 45 11 0.0868
LILRA3(u) / LILRA3(p) 0.666 0.097 45 11 0.0889
ALPL(u) x CA4(p) 0.335 0.097 45 11 0.0910
DEFA3(u) x FCGR3B(p) 0.335 0.097 45 11 0.0910
Table 10.4. AUC of combinations of 3 plasma proteins. An AUC < 0.5 indicates protein concentrations are generally lower in patients with appendicitis. P-values for the null hypothesis of AUC = 0.5 are reported.
3-Marker CombinationAUCSENDDp
ALPL x CA4 x DEFA3 0.287 0.094 45 11 0.0239
ALPL x DEFA3 x LILRA3 0.291 0.095 45 11 0.0272
CA4 x DEFA3 x LILRA3 0.303 0.096 45 11 0.0393
ALPL x CA4 x LILRA3 0.319 0.097 45 11 0.0612
DEFA1 x DEFA3 x LILRA3 0.323 0.097 45 11 0.0678
ALPL x CA4 x DEFA1 0.331 0.097 45 11 0.0827
CA4 x DEFA1 x LILRA3 0.331 0.097 45 11 0.0827
DEFA3 x FCGR3B x LILRA3 0.331 0.097 45 11 0.0827
CA4 x DEFA1 x DEFA3 0.335 0.097 45 11 0.0910
Table 10.5. AUC of combinations of 3 urine proteins. An AUC < 0.5 indicates protein concentrations are generally lower in patients with appendicitis. P-values for the null hypothesis of AUC = 0.5 are reported.
3-Marker CombinationAUCSENDDp
ALPL x CA4 x DEFA1 0.257 0.092 45 11 0.0079
CA4 x DEFA1 x DEFA3 0.257 0.092 45 11 0.0079
LILRA3 / (CA4 x DEFA3) 0.736 0.092 45 11 0.0105
LILRA3 / (ALPL x DEFA3) 0.735 0.092 45 11 0.0109
LILRA3 / (ALPL x FCGR3B) 0.732 0.093 45 11 0.0122
ALPL x DEFA1 x DEFA3 0.273 0.093 45 11 0.0147
ALPL x CA4 x DEFA3 0.274 0.093 45 11 0.0153
ALPL x DEFA1 x FCGR3B 0.275 0.093 45 11 0.0158
ALPL x DEFA3 x FCGR3B 0.279 0.094 45 11 0.0182
LILRA3 / (DEFA1 x DEFA3) 0.721 0.094 45 11 0.0182
CA4 x DEFA1 x FCGR3B 0.285 0.094 45 11 0.0224
ALPL x CA4 x FCGR3B 0.287 0.094 45 11 0.0239
CA4 x DEFA3 x FCGR3B 0.292 0.095 45 11 0.0281
LILRA3 / (ALPL x CA4) 0.707 0.095 45 11 0.0290
LILRA3 / (DEFA3 x FCGR3B) 0.705 0.095 45 11 0.0309
LILRA3 / (ALPL x DEFA1) 0.703 0.095 45 11 0.0328
DEFA1 x DEFA3 x FCGR3B 0.299 0.095 45 11 0.0349
LILRA3 / (CA4 x FCGR3B) 0.690 0.096 45 11 0.0479
LILRA3 / (DEFA1 x FCGR3B) 0.683 0.096 45 11 0.0580
LILRA3 / (CA4 x DEFA1) 0.679 0.097 45 11 0.0644
Table 10.6. AUC of combinations of 3 proteins with at least 1 urine (u) and at least 1 plasma (p) protein. An AUC < 0.5 indicates protein concentrations are generally lower in patients with appendicitis. P-values for the null hypothesis of AUC = 0.5 are reported.
3-Marker CombinationAUCSENDDp
DEFA1(u) x DEFA3(p) x LILRA3(p) 0.224 0.088 45 11 0.0017
DEFA1(u) x DEFA3(u) x LILRA3(p) 0.246 0.091 45 11 0.0051
DEFA1(u) x CA4(p) x DEFA3(p) 0.246 0.091 45 11 0.0051
DEFA1(u) x CA4(p) x LILRA3(p) 0.246 0.091 45 11 0.0051
DEFA1(u) x DEFA3(u) x CA4(p) 0.253 0.091 45 11 0.0067
CA4(u) x DEFA1(u) x LILRA3(p) 0.255 0.091 45 11 0.0073
DEFA1(u) x ALPL(p) x CA4(p) 0.255 0.091 45 11 0.0073
DEFA1(u) x ALPL(p) x LILRA3(p) 0.255 0.091 45 11 0.0073
CA4(u) x DEFA3(u) x LILRA3(p) 0.261 0.092 45 11 0.0093
DEFA1(u) x DEFA3(u) x ALPL(p) 0.261 0.092 45 11 0.0093
DEFA3(u) x ALPL(p) x DEFA3(p) 0.261 0.092 45 11 0.0093
ALPL(u) x DEFA1(u) x DEFA3(p) 0.263 0.092 45 11 0.0101
ALPL(u) x DEFA1(u) x LILRA3(p) 0.265 0.092 45 11 0.0109
DEFA1(u) x DEFA3(u) x DEFA3(p) 0.265 0.092 45 11 0.0109
DEFA1(u) x CA4(p) x DEFA1(p) 0.265 0.092 45 11 0.0109
ALPL(u) x FCGR3B(u) x DEFA3(p) 0.267 0.093 45 11 0.0118
DEFA1(u) x FCGR3B(u) x LILRA3(p) 0.267 0.093 45 11 0.0118
DEFA3(u) x DEFA3(p) x LILRA3(p) 0.269 0.093 45 11 0.0127
ALPL(u) x DEFA1(u) x CA4(p) 0.271 0.093 45 11 0.0137
ALPL(u) x DEFA3(u) x DEFA3(p) 0.273 0.093 45 11 0.0147
DEFA1(u) x ALPL(p) x DEFA3(p) 0.273 0.093 45 11 0.0147
ALPL(u) x FCGR3B(u) x LILRA3(p) 0.275 0.093 45 11 0.0158
CA4(u) x DEFA1(u) x CA4(p) 0.275 0.093 45 11 0.0158
ALPL(u) x FCGR3B(u) x CA4(p) 0.277 0.094 45 11 0.0170
DEFA1(u) x DEFA1(p) x LILRA3(p) 0.277 0.094 45 11 0.0170
DEFA3(u) x ALPL(p) x CA4(p) 0.277 0.094 45 11 0.0170
DEFA3(u) x CA4(p) x DEFA3(p) 0.277 0.094 45 11 0.0170
DEFA1(u) x DEFA3(u) x DEFA1(p) 0.279 0.094 45 11 0.0182
DEFA3(u) x ALPL(p) x LILRA3(p) 0.279 0.094 45 11 0.0182
ALPL(u) x DEFA1(u) x ALPL(p) 0.281 0.094 45 11 0.0195
CA4(u) x DEFA1(u) x DEFA3(p) 0.281 0.094 45 11 0.0195
ALPL(u) x FCGR3B(u) x ALPL(p) 0.283 0.094 45 11 0.0209
CA4(u) x DEFA3(u) x DEFA3(p) 0.283 0.094 45 11 0.0209
FCGR3B(u) x DEFA3(p) x LILRA3(p) 0.283 0.094 45 11 0.0209
ALPL(u) x DEFA1(u) x DEFA1(p) 0.285 0.094 45 11 0.0224
ALPL(u) x DEFA3(p) x LILRA3(p) 0.285 0.094 45 11 0.0224
CA4(u) x DEFA3(u) x CA4(p) 0.289 0.095 45 11 0.0255
ALPL(u) x CA4(p) x DEFA3(p) 0.291 0.095 45 11 0.0272
DEFA3(u) x CA4(p) x LILRA3(p) 0.291 0.095 45 11 0.0272
ALPL(u) x ALPL(p) x DEFA3(p) 0.293 0.095 45 11 0.0290
CA4(u) x DEFA1(u) x ALPL(p) 0.293 0.095 45 11 0.0290
CA4(u) x FCGR3B(u) x LILRA3(p) 0.294 0.095 45 11 0.0299
ALPL(u) x CA4(u) x DEFA3(p) 0.295 0.095 45 11 0.0309
ALPL(u) x DEFA3(u) x LILRA3(p) 0.295 0.095 45 11 0.0309
DEFA3(u) x FCGR3B(u) x LILRA3(p) 0.295 0.095 45 11 0.0309
ALPL(u) x FCGR3B(u) x DEFA1(p) 0.299 0.095 45 11 0.0349
ALPL(u) x CA4(u) x CA4(p) 0.301 0.095 45 11 0.0370
ALPL(u) x DEFA3(u) x ALPL(p) 0.301 0.095 45 11 0.0370
CA4(u) x DEFA3(u) x ALPL(p) 0.301 0.095 45 11 0.0370
CA4(u) x FCGR3B(u) x DEFA3(p) 0.301 0.095 45 11 0.0370
DEFA1(u) x DEFA1(p) x DEFA3(p) 0.301 0.095 45 11 0.0370
DEFA3(u) x FCGR3B(u) x DEFA3(p) 0.301 0.095 45 11 0.0370
DEFA3(u) x CA4(p) x DEFA1(p) 0.301 0.095 45 11 0.0370
DEFA3(u) x DEFA1(p) x LILRA3(p) 0.301 0.095 45 11 0.0370
DEFA1(u) x FCGR3B(u) x CA4(p) 0.305 0.096 45 11 0.0416
DEFA3(u) x FCGR3B(u) x ALPL(p) 0.305 0.096 45 11 0.0416
DEFA3(u) x DEFA1(p) x DEFA3(p) 0.305 0.096 45 11 0.0416
DEFA3(u) x FCGR3B(p) x LILRA3(p) 0.306 0.096 45 11 0.0428
ALPL(u) x CA4(u) x LILRA3(p) 0.307 0.096 45 11 0.0441
CA4(u) x DEFA3(p) x LILRA3(p) 0.307 0.096 45 11 0.0441
ALPL(u) x DEFA3(u) x CA4(p) 0.309 0.096 45 11 0.0466
ALPL(u) x ALPL(p) x LILRA3(p) 0.309 0.096 45 11 0.0466
DEFA3(u) x FCGR3B(u) x CA4(p) 0.309 0.096 45 11 0.0466
ALPL(u) x CA4(p) x LILRA3(p) 0.311 0.096 45 11 0.0493
DEFA3(u) x ALPL(p) x DEFA1(p) 0.311 0.096 45 11 0.0493
FCGR3B(u) x ALPL(p) x LILRA3(p) 0.311 0.096 45 11 0.0493
ALPL(u) x CA4(u) x ALPL(p) 0.313 0.096 45 11 0.0521
DEFA3(u) x FCGR3B(u) x DEFA1(p) 0.313 0.096 45 11 0.0521
ALPL(u) x DEFA1(u) x FCGR3B(p) 0.315 0.096 45 11 0.0550
DEFA1(u) x FCGR3B(p) x LILRA3(p) 0.315 0.096 45 11 0.0550
FCGR3B(u) x DEFA1(p) x LILRA3(p) 0.315 0.096 45 11 0.0550
FCGR3B(u) x ALPL(p) x DEFA3(p) 0.315 0.096 45 11 0.0550
CA4(u) x DEFA3(u) x DEFA1(p) 0.317 0.096 45 11 0.0580
DEFA1(u) x ALPL(p) x DEFA1(p) 0.317 0.096 45 11 0.0580
ALPL(u) x ALPL(p) x CA4(p) 0.319 0.097 45 11 0.0612
DEFA1(u) x DEFA3(u) x FCGR3B(p) 0.319 0.097 45 11 0.0612
FCGR3B(u) x CA4(p) x LILRA3(p) 0.319 0.097 45 11 0.0612
LILRA3(u) / (DEFA1(p) x LILRA3(p)) 0.681 0.097 45 11 0.0612
ALPL(u) x FCGR3B(p) x LILRA3(p) 0.321 0.097 45 11 0.0644
CA4(u) x CA4(p) x LILRA3(p) 0.323 0.097 45 11 0.0678
DEFA1(u) x FCGR3B(u) x ALPL(p) 0.323 0.097 45 11 0.0678
FCGR3B(u) x CA4(p) x DEFA3(p) 0.323 0.097 45 11 0.0678
DEFA3(u) x CA4(p) x FCGR3B(p) 0.325 0.097 45 11 0.0714
ALPL(u) x FCGR3B(u) x FCGR3B(p) 0.326 0.097 45 11 0.0732
ALPL(u) x DEFA1(p) x LILRA3(p) 0.327 0.097 45 11 0.0750
DEFA1(u) x FCGR3B(u) x DEFA3(p) 0.327 0.097 45 11 0.0750
ALPL(u) x DEFA1(p) x DEFA3(p) 0.329 0.097 45 11 0.0788
CA4(u) x DEFA1(u) x DEFA1(p) 0.329 0.097 45 11 0.0788
CA4(u) x FCGR3B(u) x CA4(p) 0.329 0.097 45 11 0.0788
CA4(u) x DEFA3(u) x FCGR3B(p) 0.332 0.097 45 11 0.0848
ALPL(u) x DEFA3(u) x DEFA1(p) 0.333 0.097 45 11 0.0868
DEFA1(u) x DEFA3(p) x FCGR3B(p) 0.333 0.097 45 11 0.0868
ALPL(u) x CA4(u) x DEFA1(p) 0.335 0.097 45 11 0.0910
DEFA3(u) x DEFA3(p) x FCGR3B(p) 0.335 0.097 45 11 0.0910
ALPL(u) x CA4(p) x DEFA1(p) 0.337 0.098 45 11 0.0954
ALPL(u) x DEFA3(p) x FCGR3B(p) 0.337 0.098 45 11 0.0954
CA4(u) x FCGR3B(u) x ALPL(p) 0.337 0.098 45 11 0.0954
DEFA1(u) x CA4(p) x FCGR3B(p) 0.337 0.098 45 11 0.0954
FCGR3B(u) x ALPL(p) x CA4(p) 0.337 0.098 45 11 0.0954
ALPL(u) x DEFA3(u) x FCGR3B(p) 0.338 0.098 45 11 0.0976
ALPL(u) x ALPL(p) x DEFA1(p) 0.339 0.098 45 11 0.0999
FCGR3B(u) x DEFA1(p) x DEFA3(p) 0.339 0.098 45 11 0.0999
Table 11.1. Confusion table and odds ratio for appendicitis using plasma protein combination ALPL x DEFA3. A cutoff concentration of 1526 (ng/mL)2 is selected corresponding to the 50th percentile.
 Adjudication 
ALPLxDEFA3ABDAppyTotal
<= cutoff 18 10 28
> cutoff 27 1 28
Total 45 11 56


[0112] Odds ratio (95% CI) = 15.0 (2.2 - 98.3), where Odds ratio = Odds below cutoff / Odds above cutoff.
Table 11.2. Confusion table and odds ratio for appendicitis using urine protein combination ALPL x DEFA1. A cutoff concentration of 50.7 (ng/mL)2 is selected corresponding to the 60th percentile.
 Adjudication 
ALPLxDEFA1ABDAppyTotal
<= cutoff 24 10 34
> cutoff 21 1 22
Total 45 11 56


[0113] Odds ratio (95% CI) = 8.8 (1.3 - 57.2), where Odds ratio = Odds below cutoff / Odds above cutoff.
Table 11.3. Confusion table and odds ratio for appendicitis using DEFA1(u) x DEFA3(p) x LILRA3(p). A cutoff concentration of 3.97 (ng/mL)3 is selected corresponding to the 50th percentile.
 Adjudication 
DEFA1(u)xDEFA3(p)xLILRA3(p)ABDAppyTotal
<= cutoff 19 9 28
> cutoff 26 2 28
Total 45 11 56


[0114] Odds ratio (95% CI) = 6.2 (1.3 - 28.3), where Odds ratio = Odds below cutoff / Odds above cutoff.

[0115] The embodiments illustrated and discussed in this specification are intended only to teach those skilled in the art how to make and use the invention. In describing embodiments of the invention, specific terminology is employed for the sake of clarity. However, the invention is not intended to be limited to the specific terminology so selected. The above-described embodiments of the invention may be modified or varied, without departing from the invention, as appreciated by those skilled in the art in light of the above teachings. It is therefore to be understood that, within the scope of the claims and their equivalents, the invention may be practiced otherwise than as specifically described.

Preferred Embodiments:



[0116] 
  1. (1) A method of diagnosing appendicitis in a subject, or assigning a likelihood of a future outcome to a subject diagnosed with appendicitis, comprising:

    performing one or more assays configured to detect one or more biomarkers selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor β, Fc frag of IgG receptor IIIb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha 1B, Defensin alpha 3, 18S ribosomal RNA, CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein P1, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32 on a body fluid sample obtained from the subject to provide one or more assay result(s); and

    correlating the assay result(s) to the occurrence or nonoccurrence of appendicitis in the subject or likelihood of the future outcome to the subject.

  2. (2) A method according to (1), wherein the performing step comprises introducing the body fluid sample obtained from the subject into an assay instrument which (i) contacts the body fluid sample with one or more binding reagents corresponding to the biomarker(s) being assayed, wherein each biomarker which is assayed binds to its respective specific binding reagent in an amount related to its concentration in the body fluid sample, (ii) generates one or more assay results indicative of binding of each biomarker which is assayed to its respective specific binding reagent; and (iii) displays the one or more assay results as a quantitative result in a human-readable form.
  3. (3) A method according to (2), wherein the specific binding reagent is an antibody.
  4. (4) A method according to (1)-(3), wherein the one or more assays are sandwich assays.
  5. (5) A method according to (1)-(4), wherein the correlating step comprises comparing the assay result(s) or a value derived therefrom to a threshold selected in a population study to separate the population into a first subpopulation at higher predisposition for the occurrence of appendicitis or the future outcome, and a second subpopulation at lower predisposition for the occurrence of appendicitis or the future outcome relative to the first subpopulation.
  6. (6) A method according to (1)-(5), further comprising treating the subject based on the predetermined subpopulation of individuals to which the patient is assigned, wherein if the patient is in the first subpopulation, the treatment comprises treating the subject for appendicitis or the future outcome.
  7. (7) A method according to (1)-(6), wherein the future outcome is mortality.
  8. (8) A method according to (1)-(6), wherein the subject is being evaluated for abdominal pain.
  9. (9) A method according to (1)-(8), wherein the correlating step comprises determining the concentration of each biomarker which is assayed, and individually comparing each biomarker concentration to a corresponding threshold level for that biomarker.
  10. (10) A method according to (1)-(9), wherein the assay instrument comprises a processing system configured to perform the correlating step and output the assay result(s) or a value derived therefrom in human readable form.
  11. (11) A method according to (2)-(10), wherein a plurality of the biomarkers are measured, wherein the assay instrument performs the correlating step, which comprises determining the concentration of each of the plurality of biomarkers, calculating a single value based on the concentration of each of the plurality of biomarkers, comparing the single value to a corresponding threshold level and displaying an indication of whether the single value does or does not exceed its corresponding threshold in a human-readable form.
  12. (12) A method according to (1)-(11), wherein method provides a sensitivity or specificity of at least 0.7 for the identification of appendicitis when compared to normal subjects.
  13. (13) A method according to (1)-(11), wherein method provides a sensitivity or specificity of at least 0.7 for the identification of appendicitis when compared to subjects exhibiting symptoms that mimic appendicitis symptoms.
  14. (14) A method according to (1)-(13), wherein the sample is selected from the group consisting of blood, serum, and plasma.
  15. (15) A method according to (1)-(13), wherein the sample is urine.
  16. (16) A method for evaluating biomarker levels in a body fluid sample, comprising:

    obtaining a body fluid sample from a subject selected for evaluation based on a determination that the subject is experiencing symptoms indicative of possible acute appendicitis; and

    performing one or more analyte binding assays configured to detect one or more biomarkers selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor β, Fc frag of IgG receptor IIIb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha 1B, Defensin alpha 3, 18S ribosomal RNA, CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein P1, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32 by introducing the body fluid sample obtained from the subject into an assay instrument which

    1. (i) contacts the body fluid sample with one or more binding reagents corresponding to the biomarker(s) being assayed, wherein each biomarker which is assayed binds to its respective specific binding reagent in an amount related to its concentration in the body fluid sample,
    2. (ii) generates one or more assay results indicative of binding of each biomarker which is assayed to its respective specific binding reagent; and
    3. (iii) displays the one or more assay results as a quantitative result in a human-readable form.

  17. (17) A method according to (16), wherein the assay result(s) are displayed as a concentration of each biomarker which is assayed.
  18. (18) A method according to (17), wherein the assay instrument further individually compares each biomarker concentration to a corresponding threshold level for that biomarker, and displays an indication of whether each biomarker does or does not exceed its corresponding threshold in a human-readable form.
  19. (19) A method according to (16), wherein a plurality of the biomarkers are measured, and wherein the assay results(s) comprise a single value calculated using a function that converts the concentration of each of the plurality of biomarkers into a single value.
  20. (20) A method according to (19), wherein the assay instrument further compares the single value to a corresponding threshold level and displays an indication of whether the single value does or does not exceed its corresponding threshold in a human-readable form.
  21. (21) A method according to (16)-(20), wherein the subject is selected for evaluation of a mortality risk within a period selected from the group consisting of 21 days, 14 days, 7 days, 5 days, 96 hours, 72 hours, 48 hours, 36 hours, 24 hours, and 12 hours.
  22. (22) A method according to (1)-(21), wherein the plurality of assays are immunoassays performed by (i) introducing the body fluid sample into an assay device comprising a plurality of antibodies, at least one of which binds to each biomarker which is assayed, and (ii) generating an assay result indicative of binding of each biomarker to its respective antibody.
  23. (23) A system for evaluating biomarker levels, comprising:

    a plurality of reagents which specifically bind for detection a plurality of biomarkers selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor β, Fc frag of IgG receptor IIIb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha 1B, Defensin alpha 3, 18S ribosomal RNA, CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein P1, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32; and

    an assay instrument configured to (i) receive a body fluid sample, (ii) contact the plurality of reagents with the body fluid sample and (iii) generate and quantitatively display in human readable form one or more assay results indicative of binding of each biomarker which is assayed to a respective specific binding reagent in the plurality of reagents.

  24. (24) A system according to (23) wherein the reagents comprise a plurality of antibodies, at least one of which binds to each of the biomarkers which are assayed.
  25. (25) A system according to (24) wherein assay instrument comprises an assay device and an assay device reader, wherein the plurality of antibodies are immobilized at a plurality of predetermined locations within the assay device, wherein the assay device is configured to receive the body fluid sample such that the body fluid sample contacts the plurality of predetermined locations, and wherein the assay device reader interrogates the plurality of predetermined locations to generate the assay results.
  26. (26) Use of one or more reagents which specifically bind for detection one or more biomarkers selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor β, Fc frag of IgG receptor IIIb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha 1B, Defensin alpha 3, 18S ribosomal RNA, CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein P1, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32 for the diagnosis of appendicitis.
  27. (27) Use of one or more biomarkers selected from the group consisting of Chemokine C-X-C receptor 1, Interleukin 8 receptor β, Fc frag of IgG receptor IIIb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha 1B, Defensin alpha 3, 18S ribosomal RNA, CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein P1, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32 for the diagnosis of appendicitis.



Claims

1. A method of diagnosing appendicitis in a subject, or assigning a likelihood of a future outcome to a subject diagnosed with appendicitis, comprising:

performing one or more assays configured to detect one or more biomarkers selected from the group consisting of Interleukin 8 receptor β, Chemokine C-X-C receptor 1, Fc frag of IgG receptor IIIb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha 1B, Defensin alpha 3, 18S ribosomal RNA, CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein P1, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32 on a body fluid sample obtained from the subject to provide one or more assay result(s); and

correlating the assay result(s) to the occurrence or nonoccurrence of appendicitis in the subject or likelihood of the future outcome to the subject.


 
2. A method according to claim 1, wherein the performing step comprises introducing the body fluid sample obtained from the subject into an assay instrument which (i) contacts the body fluid sample with one or more binding reagents corresponding to the biomarker(s) being assayed, wherein each biomarker which is assayed binds to its respective specific binding reagent in an amount related to its concentration in the body fluid sample, (ii) generates one or more assay results indicative of binding of each biomarker which is assayed to its respective specific binding reagent; and (iii) displays the one or more assay results as a quantitative result in a human-readable form, preferably
wherein the specific binding reagent is an antibody and/or
wherein the one or more assays are sandwich assays.
 
3. A method according to claim 1 or 2, wherein the correlating step comprises comparing the assay result(s) or a value derived therefrom to a threshold selected in a population study to separate the population into a first subpopulation at higher predisposition for the occurrence of appendicitis or the future outcome, and a second subpopulation at lower predisposition for the occurrence of appendicitis or the future outcome relative to the first subpopulation.
 
4. A method according to one of claims 1-3, wherein

(i) the future outcome is mortality,

(ii) wherein the subject is being evaluated for abdominal pain, or

(iii) wherein the correlating step comprises determining the concentration of each biomarker which is assayed, and individually comparing each biomarker concentration to a corresponding threshold level for that biomarker.


 
5. A method according to one of claims 3-4, wherein

(i) the assay instrument comprises a processing system configured to perform the correlating step and output the assay result(s) or a value derived therefrom in human readable form, or

(ii) a plurality of the biomarkers are measured, wherein the assay instrument performs the correlating step, which comprises determining the concentration of each of the plurality of biomarkers, calculating a single value based on the concentration of each of the plurality of biomarkers, comparing the single value to a corresponding threshold level and displaying an indication of whether the single value does or does not exceed its corresponding threshold in a human-readable form.


 
6. A method according to one of claims 1-5, wherein

(i) method provides a sensitivity or specificity of at least 0.7 for the identification of appendicitis when compared to normal subjects, or

(ii) wherein method provides a sensitivity or specificity of at least 0.7 for the identification of appendicitis when compared to subjects exhibiting symptoms that mimic appendicitis symptoms.


 
7. A method according to one of claims 1-6, wherein the sample is selected from the group consisting of blood, serum, and plasma, preferably
wherein the sample is urine.
 
8. A method for evaluating biomarker levels in a body fluid sample, comprising:

obtaining a body fluid sample from a subject selected for evaluation based on a determination that the subject is experiencing symptoms indicative of possible acute appendicitis; and

performing one or more analyte binding assays configured to detect one or more biomarkers selected from the group consisting of Interleukin 8 receptor β, Chemokine C-X-C receptor 1, Fc frag of IgG receptor IIIb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha 1B, Defensin alpha 3, 18S ribosomal RNA, CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein P1, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32 by introducing the body fluid sample obtained from the subject into an assay instrument which

(i) contacts the body fluid sample with one or more binding reagents corresponding to the biomarker(s) being assayed, wherein each biomarker which is assayed binds to its respective specific binding reagent in an amount related to its concentration in the body fluid sample,

(ii) generates one or more assay results indicative of binding of each biomarker which is assayed to its respective specific binding reagent; and

(iii) displays the one or more assay results as a quantitative result in a human-readable form.


 
9. A method according to claim 8, wherein the assay result(s) are displayed as a concentration of each biomarker which is assayed, preferably
wherein the assay instrument further individually compares each biomarker concentration to a corresponding threshold level for that biomarker, and displays an indication of whether each biomarker does or does not exceed its corresponding threshold in a human-readable form.
 
10. A method according to claim 8, wherein a plurality of the biomarkers are measured, and wherein the assay results(s) comprise a single value calculated using a function that converts the concentration of each of the plurality of biomarkers into a single value, preferably
wherein the assay instrument further compares the single value to a corresponding threshold level and displays an indication of whether the single value does or does not exceed its corresponding threshold in a human-readable form.
 
11. A method according to one of claims 8-10, wherein the subject is selected for evaluation of a mortality risk within a period selected from the group consisting of 21 days, 14 days, 7 days, 5 days, 96 hours, 72 hours, 48 hours, 36 hours, 24 hours, and 12 hours.
 
12. A method according to one of claims 1-11, wherein the plurality of assays are immunoassays performed by (i) introducing the body fluid sample into an assay device comprising a plurality of antibodies, at least one of which binds to each biomarker which is assayed, and (ii) generating an assay result indicative of binding of each biomarker to its respective antibody.
 
13. A system for evaluating biomarker levels, comprising:

a plurality of reagents which specifically bind for detection a plurality of biomarkers selected from the group consisting of Interleukin 8 receptor β, Chemokine C-X-C receptor 1, Fc frag of IgG receptor IIIb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha 1B, Defensin alpha 3, 18S ribosomal RNA, CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein P1, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32; and

an assay instrument configured to (i) receive a body fluid sample, (ii) contact the plurality of reagents with the body fluid sample and (iii) generate and quantitatively display in human readable form one or more assay results indicative of binding of each biomarker which is assayed to a respective specific binding reagent in the plurality of reagents, preferably

wherein the reagents comprise a plurality of antibodies, at least one of which binds to each of the biomarkers which are assayed, more preferably

wherein assay instrument comprises an assay device and an assay device reader, wherein the plurality of antibodies are immobilized at a plurality of predetermined locations within the assay device, wherein the assay device is configured to receive the body fluid sample such that the body fluid sample contacts the plurality of predetermined locations, and wherein the assay device reader interrogates the plurality of predetermined locations to generate the assay results.


 
14. Use of one or more reagents which specifically bind for detection one or more biomarkers selected from the group consisting of Interleukin 8 receptor β, Chemokine C-X-C receptor 1, Fc frag of IgG receptor IIIb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha 1B, Defensin alpha 3, 18S ribosomal RNA, CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein P1, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32 for the diagnosis of appendicitis.
 
15. Use of one or more biomarkers selected from the group consisting of Interleukin 8 receptor β, Chemokine C-X-C receptor 1, Fc frag of IgG receptor IIIb (CD16b), MHC class II DR beta 5, Leukocyte IgG-like receptor A3, Defensin alpha 1, Defensin alpha 1B, Defensin alpha 3, 18S ribosomal RNA, CDC14A, 28S ribosomal RNA, 60S acidic ribosomal protein P1, 40S ribosomal protein S26, Ribosomal protein L23, Ribosomal protein L37a, Ribosomal protein S28, Alkaline phosphatase, Carbonic anhydrase IV, Neuroblastoma breakpoint family 10, Ninjurin 1, Prokineticin 2, Superoxide dismutase 2, LOC100129902, LOC100131205, LOC100131905, LOC100132291, LOC100132394, LOC100132742, LOC100134364, LOC391370, LOC646785, LOC644191 and C5orf32 for the diagnosis of appendicitis.
 




Drawing


























Cited references

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